| 01 - Part 1_ Introduction | |||
| 001 A Practical Example_ What You Will Learn in This Course.mp4 | 13.08 MB | ||
| 001 A Practical Example_ What You Will Learn in This Course__en.srt | 6.41 KB | ||
| 002 What Does the Course Cover.mp4 | 49.69 MB | ||
| 002 What Does the Course Cover__en.srt | 5.1 KB | ||
| 003 Download All Resources and Important FAQ.html | 21.36 KB | ||
| 16507136-FAQ-The-Data-Science-Course.pdf | 306.1 KB | ||
| external-assets-links.txt | 101 B | ||
| 02 - The Field of Data Science - The Various Data Science Disciplines | |||
| 001 Data Science and Business Buzzwords_ Why are there so Many_.mp4 | 54.72 MB | ||
| 001 Data Science and Business Buzzwords_ Why are there so Many___en.srt | 6.77 KB | ||
| 002 What is the difference between Analysis and Analytics.mp4 | 8.01 MB | ||
| 002 What is the difference between Analysis and Analytics__en.srt | 5.03 KB | ||
| 003 Business Analytics, Data Analytics, and Data Science_ An Introduction.mp4 | 49.96 MB | ||
| 003 Business Analytics, Data Analytics, and Data Science_ An Introduction__en.srt | 11 KB | ||
| 004 Continuing with BI, ML, and AI.mp4 | 35.94 MB | ||
| 004 Continuing with BI, ML, and AI__en.srt | 11.96 KB | ||
| 005 A Breakdown of our Data Science Infographic.mp4 | 33.95 MB | ||
| 005 A Breakdown of our Data Science Infographic__en.srt | 5.21 KB | ||
| 13075156-365-DataScience-Diagram.pdf | 323.08 KB | ||
| 13075162-365-DataScience-Diagram.pdf | 323.08 KB | ||
| 13075166-365-DataScience.png | 6.92 MB | ||
| 13075168-365-DataScience.png | 6.92 MB | ||
| 03 - The Field of Data Science - Connecting the Data Science Disciplines | |||
| 001 Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4 | 21.73 MB | ||
| 001 Applying Traditional Data, Big Data, BI, Traditional Data Science and ML__en.srt | 9.14 KB | ||
| 04 - The Field of Data Science - The Benefits of Each Discipline | |||
| 001 The Reason Behind These Disciplines.mp4 | 12.41 MB | ||
| 001 The Reason Behind These Disciplines__en.srt | 6.56 KB | ||
| 05 - The Field of Data Science - Popular Data Science Techniques | |||
| 001 Techniques for Working with Traditional Data.mp4 | 105.52 MB | ||
| 001 Techniques for Working with Traditional Data__en.srt | 10.7 KB | ||
| 002 Real Life Examples of Traditional Data.mp4 | 13.92 MB | ||
| 002 Real Life Examples of Traditional Data__en.srt | 2.22 KB | ||
| 003 Techniques for Working with Big Data.mp4 | 60.48 MB | ||
| 003 Techniques for Working with Big Data__en.srt | 5.74 KB | ||
| 004 Real Life Examples of Big Data.mp4 | 4.21 MB | ||
| 004 Real Life Examples of Big Data__en.srt | 1.9 KB | ||
| 005 Business Intelligence (BI) Techniques.mp4 | 51.34 MB | ||
| 005 Business Intelligence (BI) Techniques__en.srt | 8.92 KB | ||
| 006 Real Life Examples of Business Intelligence (BI).mp4 | 19.35 MB | ||
| 006 Real Life Examples of Business Intelligence (BI)__en.srt | 2.14 KB | ||
| 007 Techniques for Working with Traditional Methods.mp4 | 74.75 MB | ||
| 007 Techniques for Working with Traditional Methods__en.srt | 11.32 KB | ||
| 008 Real Life Examples of Traditional Methods.mp4 | 21.17 MB | ||
| 008 Real Life Examples of Traditional Methods__en.srt | 3.53 KB | ||
| 009 Machine Learning (ML) Techniques.mp4 | 47.78 MB | ||
| 009 Machine Learning (ML) Techniques__en.srt | 8.94 KB | ||
| 010 Types of Machine Learning.mp4 | 61.78 MB | ||
| 010 Types of Machine Learning__en.srt | 10.46 KB | ||
| 011 Real Life Examples of Machine Learning (ML).mp4 | 22.44 MB | ||
| 011 Real Life Examples of Machine Learning (ML)__en.srt | 2.96 KB | ||
| 06 - The Field of Data Science - Popular Data Science Tools | |||
| 001 Necessary Programming Languages and Software Used in Data Science.mp4 | 19.54 MB | ||
| 001 Necessary Programming Languages and Software Used in Data Science__en.srt | 7.35 KB | ||
| 07 - The Field of Data Science - Careers in Data Science | |||
| 001 Finding the Job - What to Expect and What to Look for.mp4 | 9.48 MB | ||
| 001 Finding the Job - What to Expect and What to Look for__en.srt | 4.34 KB | ||
| 08 - The Field of Data Science - Debunking Common Misconceptions | |||
| 001 Debunking Common Misconceptions.mp4 | 16.43 MB | ||
| 001 Debunking Common Misconceptions__en.srt | 5.43 KB | ||
| 09 - Part 2_ Probability | |||
| 001 The Basic Probability Formula.mp4 | 29.13 MB | ||
| 001 The Basic Probability Formula__en.srt | 9.04 KB | ||
| 002 Computing Expected Values.mp4 | 29.24 MB | ||
| 002 Computing Expected Values__en.srt | 6.71 KB | ||
| 003 Frequency.mp4 | 36.39 MB | ||
| 003 Frequency__en.srt | 6.28 KB | ||
| 004 Events and Their Complements.mp4 | 11.4 MB | ||
| 004 Events and Their Complements__en.srt | 7.16 KB | ||
| 17431614-Course-Notes-Basic-Probability.pdf | 371.05 KB | ||
| 10 - Probability - Combinatorics | |||
| 001 Fundamentals of Combinatorics.mp4 | 3.21 MB | ||
| 001 Fundamentals of Combinatorics__en.srt | 1.35 KB | ||
| 002 Permutations and How to Use Them.mp4 | 13.97 MB | ||
| 002 Permutations and How to Use Them__en.srt | 4.24 KB | ||
| 003 Simple Operations with Factorials.mp4 | 13.98 MB | ||
| 003 Simple Operations with Factorials__en.srt | 3.56 KB | ||
| 004 Solving Variations with Repetition.mp4 | 13.75 MB | ||
| 004 Solving Variations with Repetition__en.srt | 3.64 KB | ||
| 005 Solving Variations without Repetition.mp4 | 14.76 MB | ||
| 005 Solving Variations without Repetition__en.srt | 4.74 KB | ||
| 006 Solving Combinations.mp4 | 18.99 MB | ||
| 006 Solving Combinations__en.srt | 5.72 KB | ||
| 007 Symmetry of Combinations.mp4 | 13.51 MB | ||
| 007 Symmetry of Combinations__en.srt | 4.22 KB | ||
| 008 Solving Combinations with Separate Sample Spaces.mp4 | 12.87 MB | ||
| 008 Solving Combinations with Separate Sample Spaces__en.srt | 3.81 KB | ||
| 009 Combinatorics in Real-Life_ The Lottery.mp4 | 16.16 MB | ||
| 009 Combinatorics in Real-Life_ The Lottery__en.srt | 4.16 KB | ||
| 010 A Recap of Combinatorics.mp4 | 12 MB | ||
| 010 A Recap of Combinatorics__en.srt | 3.72 KB | ||
| 011 A Practical Example of Combinatorics.mp4 | 42.24 MB | ||
| 011 A Practical Example of Combinatorics__en.srt | 14.09 KB | ||
| 17431618-Course-Notes-Combinatorics.pdf | 226.12 KB | ||
| 17431624-Symmetry-Explained.pdf | 85.04 KB | ||
| 17550452-Combinations-With-Repetition.pdf | 207.41 KB | ||
| 17756226-Additional-Exercises-Combinatorics.pdf | 106.58 KB | ||
| 19540858-Additional-Exercises-Combinatorics-Solutions.pdf | 245.67 KB | ||
| 11 - Probability - Bayesian Inference | |||
| 001 Sets and Events.mp4 | 17.44 MB | ||
| 001 Sets and Events__en.srt | 5.37 KB | ||
| 002 Ways Sets Can Interact.mp4 | 19.02 MB | ||
| 002 Ways Sets Can Interact__en.srt | 4.4 KB | ||
| 003 Intersection of Sets.mp4 | 8.78 MB | ||
| 003 Intersection of Sets__en.srt | 2.49 KB | ||
| 004 Union of Sets.mp4 | 19.47 MB | ||
| 004 Union of Sets__en.srt | 6.08 KB | ||
| 005 Mutually Exclusive Sets.mp4 | 5.25 MB | ||
| 005 Mutually Exclusive Sets__en.srt | 2.65 KB | ||
| 006 Dependence and Independence of Sets.mp4 | 11.98 MB | ||
| 006 Dependence and Independence of Sets__en.srt | 3.46 KB | ||
| 007 The Conditional Probability Formula.mp4 | 16.33 MB | ||
| 007 The Conditional Probability Formula__en.srt | 5.27 KB | ||
| 008 The Law of Total Probability.mp4 | 11.39 MB | ||
| 008 The Law of Total Probability__en.srt | 3.38 KB | ||
| 009 The Additive Rule.mp4 | 10.89 MB | ||
| 009 The Additive Rule__en.srt | 2.79 KB | ||
| 010 The Multiplication Law.mp4 | 19.8 MB | ||
| 010 The Multiplication Law__en.srt | 4.66 KB | ||
| 011 Bayes' Law.mp4 | 20.94 MB | ||
| 011 Bayes' Law__en.srt | 7.55 KB | ||
| 012 A Practical Example of Bayesian Inference.mp4 | 125.49 MB | ||
| 012 A Practical Example of Bayesian Inference__en.srt | 19.75 KB | ||
| 17431622-Course-Notes-Bayesian-Inference.pdf | 386.01 KB | ||
| 17970686-CDS-2017-2018-Hamilton.pdf | 845.31 KB | ||
| 18886388-Bayesian-Homework.pdf | 27.26 KB | ||
| 18886392-Bayesian-Homework-Solutions.pdf | 30.35 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 12 - Probability - Distributions | |||
| 001 Fundamentals of Probability Distributions.mp4 | 19.28 MB | ||
| 001 Fundamentals of Probability Distributions__en.srt | 7.92 KB | ||
| 002 Types of Probability Distributions.mp4 | 28.69 MB | ||
| 002 Types of Probability Distributions__en.srt | 9.72 KB | ||
| 003 Characteristics of Discrete Distributions.mp4 | 9.25 MB | ||
| 003 Characteristics of Discrete Distributions__en.srt | 2.51 KB | ||
| 004 Discrete Distributions_ The Uniform Distribution.mp4 | 10.08 MB | ||
| 004 Discrete Distributions_ The Uniform Distribution__en.srt | 2.84 KB | ||
| 005 Discrete Distributions_ The Bernoulli Distribution.mp4 | 14.76 MB | ||
| 005 Discrete Distributions_ The Bernoulli Distribution__en.srt | 4.29 KB | ||
| 006 Discrete Distributions_ The Binomial Distribution.mp4 | 24.94 MB | ||
| 006 Discrete Distributions_ The Binomial Distribution__en.srt | 8.68 KB | ||
| 007 Discrete Distributions_ The Poisson Distribution.mp4 | 14.62 MB | ||
| 007 Discrete Distributions_ The Poisson Distribution__en.srt | 6.6 KB | ||
| 008 Characteristics of Continuous Distributions.mp4 | 28.87 MB | ||
| 008 Characteristics of Continuous Distributions__en.srt | 8.88 KB | ||
| 009 Continuous Distributions_ The Normal Distribution.mp4 | 19.67 MB | ||
| 009 Continuous Distributions_ The Normal Distribution__en.srt | 4.92 KB | ||
| 010 Continuous Distributions_ The Standard Normal Distribution.mp4 | 20.72 MB | ||
| 010 Continuous Distributions_ The Standard Normal Distribution__en.srt | 5.41 KB | ||
| 011 Continuous Distributions_ The Students' T Distribution.mp4 | 5.44 MB | ||
| 011 Continuous Distributions_ The Students' T Distribution__en.srt | 2.97 KB | ||
| 012 Continuous Distributions_ The Chi-Squared Distribution.mp4 | 10.95 MB | ||
| 012 Continuous Distributions_ The Chi-Squared Distribution__en.srt | 2.9 KB | ||
| 013 Continuous Distributions_ The Exponential Distribution.mp4 | 15.76 MB | ||
| 013 Continuous Distributions_ The Exponential Distribution__en.srt | 4.2 KB | ||
| 014 Continuous Distributions_ The Logistic Distribution.mp4 | 15.95 MB | ||
| 014 Continuous Distributions_ The Logistic Distribution__en.srt | 5.42 KB | ||
| 015 A Practical Example of Probability Distributions.mp4 | 138.31 MB | ||
| 015 A Practical Example of Probability Distributions__en.srt | 20.29 KB | ||
| 17431628-Solving-Integrals.pdf | 343.85 KB | ||
| 17550252-Normal-Distribution-Exp-and-Var.pdf | 144.08 KB | ||
| 17862366-Poisson-Expected-Value-and-Variance.pdf | 145.99 KB | ||
| 17971238-FIFA19.csv | 8.64 MB | ||
| 17971248-FIFA19-post.csv | 8.64 MB | ||
| 17971258-Daily-Views.xlsx | 9.53 KB | ||
| 17971260-Daily-Views-post.xlsx | 20.21 KB | ||
| 17971264-Customers-Membership.xlsx | 9.69 KB | ||
| 17971268-Customers-Membership-post.xlsx | 15.62 KB | ||
| 20945990-Course-Notes-Probability-Distributions.pdf | 463.95 KB | ||
| 13 - Probability - Probability in Other Fields | |||
| 001 Probability in Finance.mp4 | 39.66 MB | ||
| 001 Probability in Finance__en.srt | 9.8 KB | ||
| 002 Probability in Statistics.mp4 | 14.26 MB | ||
| 002 Probability in Statistics__en.srt | 8.62 KB | ||
| 003 Probability in Data Science.mp4 | 23.94 MB | ||
| 003 Probability in Data Science__en.srt | 6.64 KB | ||
| 19327638-Probability-in-Finance-Homework.pdf | 110.68 KB | ||
| 19327648-Probability-in-Finance-Solutions.pdf | 184.46 KB | ||
| 23224540-Probability-Cheat-Sheet.pdf | 320.28 KB | ||
| 14 - Part 3_ Statistics | |||
| 001 Population and Sample.mp4 | 10.89 MB | ||
| 001 Population and Sample__en.srt | 5.59 KB | ||
| 14812652-Course-notes-descriptive-statistics.pdf | 482.21 KB | ||
| 15762096-Statistics-Glossary.xlsx | 20.26 KB | ||
| 15 - Statistics - Descriptive Statistics | |||
| 001 Types of Data.mp4 | 42.47 MB | ||
| 001 Types of Data__en.srt | 6.14 KB | ||
| 002 Levels of Measurement.mp4 | 31.44 MB | ||
| 002 Levels of Measurement__en.srt | 4.72 KB | ||
| 003 Categorical Variables - Visualization Techniques.mp4 | 36.65 MB | ||
| 003 Categorical Variables - Visualization Techniques__en.srt | 6.44 KB | ||
| 004 Categorical Variables Exercise.html | 81 B | ||
| 005 Numerical Variables - Frequency Distribution Table.mp4 | 12.8 MB | ||
| 005 Numerical Variables - Frequency Distribution Table__en.srt | 4.39 KB | ||
| 006 Numerical Variables Exercise.html | 81 B | ||
| 007 The Histogram.mp4 | 3.85 MB | ||
| 007 The Histogram__en.srt | 3.12 KB | ||
| 008 Histogram Exercise.html | 81 B | ||
| 009 Cross Tables and Scatter Plots.mp4 | 19.7 MB | ||
| 009 Cross Tables and Scatter Plots__en.srt | 6.7 KB | ||
| 010 Cross Tables and Scatter Plots Exercise.html | 81 B | ||
| 011 Mean, median and mode.mp4 | 17.53 MB | ||
| 011 Mean, median and mode__en.srt | 5.99 KB | ||
| 012 Mean, Median and Mode Exercise.html | 81 B | ||
| 013 Skewness.mp4 | 9.92 MB | ||
| 013 Skewness__en.srt | 3.63 KB | ||
| 014 Skewness Exercise.html | 81 B | ||
| 015 Variance.mp4 | 20.21 MB | ||
| 015 Variance__en.srt | 7.87 KB | ||
| 016 Variance Exercise.html | 522 B | ||
| 017 Standard Deviation and Coefficient of Variation.mp4 | 20.14 MB | ||
| 017 Standard Deviation and Coefficient of Variation__en.srt | 6.62 KB | ||
| 018 Standard Deviation and Coefficient of Variation Exercise.html | 81 B | ||
| 019 Covariance.mp4 | 18.41 MB | ||
| 019 Covariance__en.srt | 4.97 KB | ||
| 020 Covariance Exercise.html | 81 B | ||
| 021 Correlation Coefficient.mp4 | 19.38 MB | ||
| 021 Correlation Coefficient__en.srt | 4.75 KB | ||
| 022 Correlation Coefficient Exercise.html | 81 B | ||
| 13055412-2.3.Categorical-variables.Visualization-techniques-exercise.xlsx | 15.24 KB | ||
| 13055414-2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx | 41.11 KB | ||
| 13055440-2.5.The-Histogram-lesson.xlsx | 18.63 KB | ||
| 13055456-2.6.Cross-table-and-scatter-plot.xlsx | 26.12 KB | ||
| 13055460-2.6.Cross-table-and-scatter-plot-exercise.xlsx | 16.28 KB | ||
| 13055464-2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx | 40.44 KB | ||
| 13055474-2.7.Mean-median-and-mode-lesson.xlsx | 10.49 KB | ||
| 13055484-2.7.Mean-median-and-mode-exercise.xlsx | 10.87 KB | ||
| 13055486-2.7.Mean-median-and-mode-exercise-solution.xlsx | 11.35 KB | ||
| 13055492-2.8.Skewness-lesson.xlsx | 34.63 KB | ||
| 13055500-2.8.Skewness-exercise.xlsx | 9.49 KB | ||
| 13055502-2.8.Skewness-exercise-solution.xlsx | 19.78 KB | ||
| 13055510-2.9.Variance-lesson.xlsx | 10.08 KB | ||
| 13055516-2.9.Variance-exercise.xlsx | 10.83 KB | ||
| 13055520-2.9.Variance-exercise-solution.xlsx | 11.05 KB | ||
| 13055774-2.3.Categorical-variables.Visualization-techniques-lesson.xlsx | 30.77 KB | ||
| 13055786-2.5.The-Histogram-exercise.xlsx | 15.5 KB | ||
| 13055790-2.5.The-Histogram-exercise-solution.xlsx | 17.1 KB | ||
| 13055800-2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx | 10.97 KB | ||
| 13055814-2.11.Covariance-lesson.xlsx | 24.92 KB | ||
| 13055822-2.11.Covariance-exercise.xlsx | 20.23 KB | ||
| 13055824-2.11.Covariance-exercise-solution.xlsx | 29.51 KB | ||
| 13055834-2.12.Correlation-exercise.xlsx | 29.3 KB | ||
| 13055838-2.12.Correlation-exercise-solution.xlsx | 29.48 KB | ||
| 14679830-2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx | 11.44 KB | ||
| 14812660-Course-notes-descriptive-statistics.pdf | 482.21 KB | ||
| 16753694-Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf | 289.12 KB | ||
| 16753696-Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf | 289.12 KB | ||
| 18029224-Glossary.xlsx | 19.97 KB | ||
| 19880121-2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx | 11.61 KB | ||
| 19880123-2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx | 12.6 KB | ||
| 23038654-2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx | 13.15 KB | ||
| 16 - Statistics - Practical Example_ Descriptive Statistics | |||
| 001 Practical Example_ Descriptive Statistics.mp4 | 37.17 MB | ||
| 001 Practical Example_ Descriptive Statistics__en.srt | 20.91 KB | ||
| 002 Practical Example_ Descriptive Statistics Exercise.html | 81 B | ||
| 13129220-2.13.Practical-example.Descriptive-statistics-lesson.xlsx | 146.51 KB | ||
| 19527574-2.13.Practical-example.Descriptive-statistics-exercise.xlsx | 120.27 KB | ||
| 19527576-2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx | 146.38 KB | ||
| 17 - Statistics - Inferential Statistics Fundamentals | |||
| 001 Introduction.mp4 | 2.93 MB | ||
| 001 Introduction__en.srt | 1.63 KB | ||
| 002 What is a Distribution.mp4 | 16.9 MB | ||
| 002 What is a Distribution__en.srt | 6.13 KB | ||
| 003 The Normal Distribution.mp4 | 16.16 MB | ||
| 003 The Normal Distribution__en.srt | 5.01 KB | ||
| 004 The Standard Normal Distribution.mp4 | 8.62 MB | ||
| 004 The Standard Normal Distribution__en.srt | 4.15 KB | ||
| 005 The Standard Normal Distribution Exercise.html | 81 B | ||
| 006 Central Limit Theorem.mp4 | 22.86 MB | ||
| 006 Central Limit Theorem__en.srt | 5.68 KB | ||
| 007 Standard error.mp4 | 13.33 MB | ||
| 007 Standard error__en.srt | 1.92 KB | ||
| 008 Estimators and Estimates.mp4 | 16.13 MB | ||
| 008 Estimators and Estimates__en.srt | 3.89 KB | ||
| 13055898-3.2.What-is-a-distribution-lesson.xlsx | 19.46 KB | ||
| 13055942-3.4.Standard-normal-distribution-lesson.xlsx | 10.38 KB | ||
| 13831264-Course-notes-inferential-statistics.pdf | 382.32 KB | ||
| 13831266-Course-notes-inferential-statistics.pdf | 382.32 KB | ||
| 14171114-3.4.Standard-normal-distribution-exercise.xlsx | 11.99 KB | ||
| 14171118-3.4.Standard-normal-distribution-exercise-solution.xlsx | 24.04 KB | ||
| 18 - Statistics - Inferential Statistics_ Confidence Intervals | |||
| 001 What are Confidence Intervals_.mp4 | 28.38 MB | ||
| 001 What are Confidence Intervals___en.srt | 3.29 KB | ||
| 002 Confidence Intervals; Population Variance Known; Z-score.mp4 | 52.21 MB | ||
| 002 Confidence Intervals; Population Variance Known; Z-score__en.srt | 10.26 KB | ||
| 003 Confidence Intervals; Population Variance Known; Z-score; Exercise.html | 81 B | ||
| 004 Confidence Interval Clarifications.mp4 | 18.56 MB | ||
| 004 Confidence Interval Clarifications__en.srt | 5.8 KB | ||
| 005 Student's T Distribution.mp4 | 13.33 MB | ||
| 005 Student's T Distribution__en.srt | 4.24 KB | ||
| 006 Confidence Intervals; Population Variance Unknown; T-score.mp4 | 11.58 MB | ||
| 006 Confidence Intervals; Population Variance Unknown; T-score__en.srt | 5.67 KB | ||
| 007 Confidence Intervals; Population Variance Unknown; T-score; Exercise.html | 81 B | ||
| 008 Margin of Error.mp4 | 22.66 MB | ||
| 008 Margin of Error__en.srt | 6.27 KB | ||
| 009 Confidence intervals. Two means. Dependent samples.mp4 | 45.04 MB | ||
| 009 Confidence intervals. Two means. Dependent samples__en.srt | 8.18 KB | ||
| 010 Confidence intervals. Two means. Dependent samples Exercise.html | 81 B | ||
| 011 Confidence intervals. Two means. Independent Samples (Part 1).mp4 | 12 MB | ||
| 011 Confidence intervals. Two means. Independent Samples (Part 1)__en.srt | 6.1 KB | ||
| 012 Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html | 81 B | ||
| 013 Confidence intervals. Two means. Independent Samples (Part 2).mp4 | 13.05 MB | ||
| 013 Confidence intervals. Two means. Independent Samples (Part 2)__en.srt | 4.81 KB | ||
| 014 Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html | 81 B | ||
| 015 Confidence intervals. Two means. Independent Samples (Part 3).mp4 | 4.17 MB | ||
| 015 Confidence intervals. Two means. Independent Samples (Part 3)__en.srt | 1.93 KB | ||
| 13056180-3.9.Population-variance-known-z-score-lesson.xlsx | 11.21 KB | ||
| 13056196-3.9.Population-variance-known-z-score-exercise.xlsx | 10.83 KB | ||
| 13056200-3.9.Population-variance-known-z-score-exercise-solution.xlsx | 11.16 KB | ||
| 13056212-3.11.Population-variance-unknown-t-score-lesson.xlsx | 10.78 KB | ||
| 13056216-3.11.The-t-table.xlsx | 15.85 KB | ||
| 13056226-3.11.Population-variance-unknown-t-score-exercise.xlsx | 10.62 KB | ||
| 13056228-3.11.Population-variance-unknown-t-score-exercise-solution.xlsx | 11.1 KB | ||
| 13056236-3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx | 10.47 KB | ||
| 13056246-3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx | 13.74 KB | ||
| 13056252-3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx | 14.24 KB | ||
| 13056280-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx | 9.83 KB | ||
| 13056290-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx | 9.83 KB | ||
| 13056292-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx | 10.12 KB | ||
| 13056308-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx | 9.52 KB | ||
| 13056316-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx | 9.17 KB | ||
| 13056318-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx | 9.79 KB | ||
| 16413674-3.9.The-z-table.xlsx | 25.58 KB | ||
| 16413678-3.9.The-z-table.xlsx | 25.58 KB | ||
| 21198408-3.11.The-t-table.xlsx | 15.85 KB | ||
| 19 - Statistics - Practical Example_ Inferential Statistics | |||
| 001 Practical Example_ Inferential Statistics.mp4 | 22.1 MB | ||
| 001 Practical Example_ Inferential Statistics__en.srt | 13.73 KB | ||
| 002 Practical Example_ Inferential Statistics Exercise.html | 81 B | ||
| 13056326-3.17.Practical-example.Confidence-intervals-lesson.xlsx | 1.74 MB | ||
| 17959056-3.17.Practical-example.Confidence-intervals-exercise.xlsx | 1.73 MB | ||
| 17959058-3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx | 1.82 MB | ||
| 20 - Statistics - Hypothesis Testing | |||
| 001 Null vs Alternative Hypothesis.mp4 | 80.83 MB | ||
| 001 Null vs Alternative Hypothesis__en.srt | 7.35 KB | ||
| 002 Further Reading on Null and Alternative Hypothesis.html | 2.23 KB | ||
| 003 Rejection Region and Significance Level.mp4 | 38.2 MB | ||
| 003 Rejection Region and Significance Level__en.srt | 9.09 KB | ||
| 004 Type I Error and Type II Error.mp4 | 18.17 MB | ||
| 004 Type I Error and Type II Error__en.srt | 5.26 KB | ||
| 005 Test for the Mean. Population Variance Known.mp4 | 36.96 MB | ||
| 005 Test for the Mean. Population Variance Known__en.srt | 8.32 KB | ||
| 006 Test for the Mean. Population Variance Known Exercise.html | 81 B | ||
| 007 p-value.mp4 | 33.08 MB | ||
| 007 p-value__en.srt | 5.37 KB | ||
| 008 Test for the Mean. Population Variance Unknown.mp4 | 19.72 MB | ||
| 008 Test for the Mean. Population Variance Unknown__en.srt | 6.2 KB | ||
| 009 Test for the Mean. Population Variance Unknown Exercise.html | 81 B | ||
| 010 Test for the Mean. Dependent Samples.mp4 | 32.8 MB | ||
| 010 Test for the Mean. Dependent Samples__en.srt | 6.78 KB | ||
| 011 Test for the Mean. Dependent Samples Exercise.html | 81 B | ||
| 012 Test for the mean. Independent Samples (Part 1).mp4 | 7.57 MB | ||
| 012 Test for the mean. Independent Samples (Part 1)__en.srt | 5.57 KB | ||
| 013 Test for the mean. Independent Samples (Part 1). Exercise.html | 81 B | ||
| 014 Test for the mean. Independent Samples (Part 2).mp4 | 24.47 MB | ||
| 014 Test for the mean. Independent Samples (Part 2)__en.srt | 5.47 KB | ||
| 015 Test for the mean. Independent Samples (Part 2). Exercise.html | 81 B | ||
| 13056520-4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx | 10.96 KB | ||
| 13056684-4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx | 11.03 KB | ||
| 13056688-4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx | 11.22 KB | ||
| 13056708-4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx | 11.34 KB | ||
| 13056712-4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx | 9.79 KB | ||
| 13056716-4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx | 12.8 KB | ||
| 13056718-4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx | 14.4 KB | ||
| 13056720-4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx | 9.63 KB | ||
| 13056726-4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx | 9.31 KB | ||
| 13737052-4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx | 14.54 KB | ||
| 16190540-4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx | 10.54 KB | ||
| 16190542-4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx | 11.39 KB | ||
| 16200120-4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx | 10.77 KB | ||
| 16753580-Online-p-value-calculator.pdf | 1.15 MB | ||
| 17710210-4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx | 12.63 KB | ||
| 18041220-4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx | 11.25 KB | ||
| 22431075-Course-notes-hypothesis-testing.pdf | 656.44 KB | ||
| 22431079-Course-notes-hypothesis-testing.pdf | 656.44 KB | ||
| 21 - Statistics - Practical Example_ Hypothesis Testing | |||
| 001 Practical Example_ Hypothesis Testing.mp4 | 16.3 MB | ||
| 001 Practical Example_ Hypothesis Testing__en.srt | 8.71 KB | ||
| 002 Practical Example_ Hypothesis Testing Exercise.html | 81 B | ||
| 27047254-4.10.Hypothesis-testing-section-practical-example.xlsx | 51.9 KB | ||
| 27047330-4.10.Hypothesis-testing-section-practical-example-exercise.xlsx | 43.69 KB | ||
| 27047334-4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx | 44.27 KB | ||
| 22 - Part 4_ Introduction to Python | |||
| 001 Introduction to Programming.mp4 | 14.33 MB | ||
| 001 Introduction to Programming__en.srt | 6.93 KB | ||
| 002 Why Python_.mp4 | 11.77 MB | ||
| 002 Why Python___en.srt | 6.85 KB | ||
| 003 Why Jupyter_.mp4 | 7.96 MB | ||
| 003 Why Jupyter___en.srt | 4.63 KB | ||
| 004 Installing Python and Jupyter.mp4 | 32.86 MB | ||
| 004 Installing Python and Jupyter__en.srt | 9.11 KB | ||
| 005 Understanding Jupyter's Interface - the Notebook Dashboard.mp4 | 4.39 MB | ||
| 005 Understanding Jupyter's Interface - the Notebook Dashboard__en.srt | 3.7 KB | ||
| 006 Prerequisites for Coding in the Jupyter Notebooks.mp4 | 15.38 MB | ||
| 006 Prerequisites for Coding in the Jupyter Notebooks__en.srt | 7.66 KB | ||
| 23 - Python - Variables and Data Types | |||
| 001 Variables.mp4 | 8.93 MB | ||
| 001 Variables__en.srt | 4.53 KB | ||
| 002 Numbers and Boolean Values in Python.mp4 | 4.61 MB | ||
| 002 Numbers and Boolean Values in Python__en.srt | 3.62 KB | ||
| 003 Python Strings.mp4 | 19.74 MB | ||
| 003 Python Strings__en.srt | 7.1 KB | ||
| 15870664-Python-Introduction-Course-Notes.pdf | 2.03 MB | ||
| 29544526-Variables-Lecture-Py3.ipynb | 3.61 KB | ||
| 29544572-Numbers-and-Boolean-Values-Lecture-Py3.ipynb | 3.36 KB | ||
| 29544578-Strings-Lecture-Py3.ipynb | 7.56 KB | ||
| 29544582-Strings-Exercise-Py3.ipynb | 2.61 KB | ||
| 29544586-Strings-Solution-Py3.ipynb | 5.45 KB | ||
| 29544590-Numbers-and-Boolean-Values-Exercise-Py3.ipynb | 2.29 KB | ||
| 29544594-Numbers-and-Boolean-Values-Solution-Py3.ipynb | 3.23 KB | ||
| 29544602-Variables-Exercise-Py3.ipynb | 2.23 KB | ||
| 29544612-Variables-Solution-Py3.ipynb | 3.79 KB | ||
| 24 - Python - Basic Python Syntax | |||
| 001 Using Arithmetic Operators in Python.mp4 | 7.28 MB | ||
| 001 Using Arithmetic Operators in Python__en.srt | 4.28 KB | ||
| 002 The Double Equality Sign.mp4 | 2.72 MB | ||
| 002 The Double Equality Sign__en.srt | 1.77 KB | ||
| 003 How to Reassign Values.mp4 | 1.86 MB | ||
| 003 How to Reassign Values__en.srt | 1.39 KB | ||
| 004 Add Comments.mp4 | 2.41 MB | ||
| 004 Add Comments__en.srt | 1.8 KB | ||
| 005 Understanding Line Continuation.mp4 | 1014.51 KB | ||
| 005 Understanding Line Continuation__en.srt | 1.14 KB | ||
| 006 Indexing Elements.mp4 | 2.36 MB | ||
| 006 Indexing Elements__en.srt | 1.63 KB | ||
| 007 Structuring with Indentation.mp4 | 2.8 MB | ||
| 007 Structuring with Indentation__en.srt | 2.18 KB | ||
| 29544616-Arithmetic-Operators-Lecture-Py3.ipynb | 3.53 KB | ||
| 29544618-Arithmetic-Operators-Exercise-Py3.ipynb | 2.62 KB | ||
| 29544620-Arithmetic-Operators-Solution-Py3.ipynb | 4.24 KB | ||
| 29544624-The-Double-Equality-Sign-Lecture-Py3.ipynb | 1.45 KB | ||
| 29544630-The-Double-Equality-Sign-Exercise-Py3.ipynb | 838 B | ||
| 29544632-The-Double-Equality-Sign-Solution-Py3.ipynb | 1.14 KB | ||
| 29544648-Reassign-Values-Lecture-Py3.ipynb | 3.08 KB | ||
| 29544656-Reassign-Values-Exercise-Py3.ipynb | 1.67 KB | ||
| 29544658-Reassign-Values-Solution-Py3.ipynb | 2.12 KB | ||
| 29544678-Add-Comments-Lecture-Py3.ipynb | 1.03 KB | ||
| 29544682-Indexing-Elements-Lecture-Py3.ipynb | 1.32 KB | ||
| 29544684-Indexing-Elements-Exercise-Py3.ipynb | 1.35 KB | ||
| 29544694-Indexing-Elements-Solution-Py3.ipynb | 2.17 KB | ||
| 29544712-Line-Continuation-Lecture-Py3.ipynb | 779 B | ||
| 29544714-Line-Continuation-Exercise-Py3.ipynb | 1.14 KB | ||
| 29544716-Line-Continuation-Solution-Py3.ipynb | 1.5 KB | ||
| 29544720-Structure-Your-Code-with-Indentation-Lecture-Py3.ipynb | 958 B | ||
| 29544724-Structure-Your-Code-with-Indentation-Exercise-Py3.ipynb | 956 B | ||
| 29544728-Structure-Your-Code-with-Indentation-Solution-Py3.ipynb | 1.5 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 25 - Python - Other Python Operators | |||
| 001 Comparison Operators.mp4 | 3.12 MB | ||
| 001 Comparison Operators__en.srt | 2.5 KB | ||
| 002 Logical and Identity Operators.mp4 | 19 MB | ||
| 002 Logical and Identity Operators__en.srt | 5.94 KB | ||
| 29544734-Comparison-Operators-Lecture-Py3.ipynb | 2.53 KB | ||
| 29544738-Comparison-Operators-Exercise-Py3.ipynb | 1.61 KB | ||
| 29544744-Comparison-Operators-Solution-Py3.ipynb | 2.41 KB | ||
| 29544754-Logical-and-Identity-Operators-Lecture-Py3.ipynb | 5.86 KB | ||
| 29544770-Logical-and-Identity-Operators-Lecture-Py3.ipynb | 5.86 KB | ||
| 29544776-Logical-and-Identity-Operators-Solution-Py3.ipynb | 3.43 KB | ||
| 26 - Python - Conditional Statements | |||
| 001 The IF Statement.mp4 | 5.33 MB | ||
| 001 The IF Statement__en.srt | 3.53 KB | ||
| 002 The ELSE Statement.mp4 | 5.25 MB | ||
| 002 The ELSE Statement__en.srt | 3.11 KB | ||
| 003 The ELIF Statement.mp4 | 14.25 MB | ||
| 003 The ELIF Statement__en.srt | 6.6 KB | ||
| 004 A Note on Boolean Values.mp4 | 3.26 MB | ||
| 004 A Note on Boolean Values__en.srt | 2.91 KB | ||
| 29544784-Introduction-to-the-If-Statement-Lecture-Py3.ipynb | 1.14 KB | ||
| 29544788-Introduction-to-the-If-Statement-Exercise-Py3.ipynb | 1.53 KB | ||
| 29544792-Introduction-to-the-If-Statement-Solution-Py3.ipynb | 2.19 KB | ||
| 29544796-Add-an-Else-Statement-Lecture-Py3.ipynb | 1.76 KB | ||
| 29544802-Add-an-Else-Statement-Exercise-Py3.ipynb | 1.02 KB | ||
| 29544804-Add-an-Else-Statement-Solution-Py3.ipynb | 1.4 KB | ||
| 29544814-Else-If-for-Brief-Elif-Lecture-Py3.ipynb | 3.24 KB | ||
| 29544818-Else-If-for-Brief-Elif-Exercise-Py3.ipynb | 1.75 KB | ||
| 29544822-Else-If-for-Brief-Elif-Solution-Py3.ipynb | 2.4 KB | ||
| 29544828-A-Note-on-Boolean-Values-Lecture-Py3.ipynb | 791 B | ||
| 27 - Python - Python Functions | |||
| 001 Defining a Function in Python.mp4 | 3.23 MB | ||
| 001 Defining a Function in Python__en.srt | 2.43 KB | ||
| 002 How to Create a Function with a Parameter.mp4 | 8.29 MB | ||
| 002 How to Create a Function with a Parameter__en.srt | 4.3 KB | ||
| 003 Defining a Function in Python - Part II.mp4 | 6.45 MB | ||
| 003 Defining a Function in Python - Part II__en.srt | 2.88 KB | ||
| 004 How to Use a Function within a Function.mp4 | 3.25 MB | ||
| 004 How to Use a Function within a Function__en.srt | 2.07 KB | ||
| 005 Conditional Statements and Functions.mp4 | 6.04 MB | ||
| 005 Conditional Statements and Functions__en.srt | 3.62 KB | ||
| 006 Functions Containing a Few Arguments.mp4 | 2.24 MB | ||
| 006 Functions Containing a Few Arguments__en.srt | 1.33 KB | ||
| 007 Built-in Functions in Python.mp4 | 8.5 MB | ||
| 007 Built-in Functions in Python__en.srt | 4.29 KB | ||
| 29544842-Defining-a-Function-in-Python-Lecture-Py3.ipynb | 868 B | ||
| 29544846-Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb | 1.59 KB | ||
| 29544848-Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb | 1.16 KB | ||
| 29544850-Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb | 1.79 KB | ||
| 29544866-Another-Way-to-Define-a-Function-Lecture-Py3.ipynb | 3.29 KB | ||
| 29544868-Another-Way-to-Define-a-Function-Exercise-Py3.ipynb | 1.24 KB | ||
| 29544874-Another-Way-to-Define-a-Function-Solution-Py3.ipynb | 1.98 KB | ||
| 29544880-0.6.4-Using-a-Function-in-another-Function-Lecture-Py3.ipynb | 1015 B | ||
| 29544888-0.6.4-Using-a-Function-in-another-Function-Exercise-Py3.ipynb | 1.04 KB | ||
| 29544890-0.6.4-Using-a-Function-in-another-Function-Solution-Py3.ipynb | 1.6 KB | ||
| 29544904-Combining-Conditional-Statements-and-Functions-Lecture-Py3.ipynb | 1.29 KB | ||
| 29544906-Combining-Conditional-Statements-and-Functions-Exercise-Py3.ipynb | 1.06 KB | ||
| 29544910-Combining-Conditional-Statements-and-Functions-Solution-Py3.ipynb | 1.65 KB | ||
| 29544920-Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb | 1.72 KB | ||
| 29544922-Notable-Built-In-Functions-in-Python-Lecture-Py3.ipynb | 4.51 KB | ||
| 29544924-Notable-Built-In-Functions-in-Python-Exercise-Py3.ipynb | 3.66 KB | ||
| 29544926-Notable-Built-In-Functions-in-Python-Solution-Py3.ipynb | 5.52 KB | ||
| 28 - Python - Sequences | |||
| 001 Lists.mp4 | 20.5 MB | ||
| 001 Lists__en.srt | 10.05 KB | ||
| 002 Using Methods.mp4 | 23.42 MB | ||
| 002 Using Methods__en.srt | 8.35 KB | ||
| 003 List Slicing.mp4 | 19.17 MB | ||
| 003 List Slicing__en.srt | 5.22 KB | ||
| 004 Tuples.mp4 | 9.5 MB | ||
| 004 Tuples__en.srt | 7.24 KB | ||
| 005 Dictionaries.mp4 | 24.91 MB | ||
| 005 Dictionaries__en.srt | 9.08 KB | ||
| 29544928-Lists-Lecture-Py3.ipynb | 2.7 KB | ||
| 29544930-Lists-Exercise-Py3.ipynb | 2.14 KB | ||
| 29544932-Lists-Solution-Py3.ipynb | 3.18 KB | ||
| 29544938-Help-Yourself-with-Methods-Lecture-Py3.ipynb | 4.39 KB | ||
| 29544942-Help-Yourself-with-Methods-Exercise-Py3.ipynb | 1.91 KB | ||
| 29544946-Help-Yourself-with-Methods-Solution-Py3.ipynb | 2.83 KB | ||
| 29544952-List-Slicing-Lecture-Py3.ipynb | 5.02 KB | ||
| 29544956-List-Slicing-Exercise-Py3.ipynb | 2.79 KB | ||
| 29544960-List-Slicing-Solution-Py3.ipynb | 4.26 KB | ||
| 29544972-Tuples-Lecture-Py3.ipynb | 2.91 KB | ||
| 29544976-Tuples-Exercise-Py3.ipynb | 2.07 KB | ||
| 29544978-Tuples-Solution-Py3.ipynb | 4.61 KB | ||
| 29544988-Dictionaries-Lecture-Py3.ipynb | 4.35 KB | ||
| 29544992-Dictionaries-Exercise-Py3.ipynb | 2.92 KB | ||
| 29544994-Dictionaries-Solution-Py3.ipynb | 6.16 KB | ||
| 29 - Python - Iterations | |||
| 001 For Loops.mp4 | 23.58 MB | ||
| 001 For Loops__en.srt | 6.69 KB | ||
| 002 While Loops and Incrementing.mp4 | 20.2 MB | ||
| 002 While Loops and Incrementing__en.srt | 6.18 KB | ||
| 003 Lists with the range() Function.mp4 | 14.5 MB | ||
| 003 Lists with the range() Function__en.srt | 8.03 KB | ||
| 004 Conditional Statements and Loops.mp4 | 21.94 MB | ||
| 004 Conditional Statements and Loops__en.srt | 7.67 KB | ||
| 005 Conditional Statements, Functions, and Loops.mp4 | 2.91 MB | ||
| 005 Conditional Statements, Functions, and Loops__en.srt | 2.33 KB | ||
| 006 How to Iterate over Dictionaries.mp4 | 16.46 MB | ||
| 006 How to Iterate over Dictionaries__en.srt | 7.6 KB | ||
| 29545008-For-Loops-Lecture-Py3.ipynb | 1.26 KB | ||
| 29545010-For-Loops-Exercise-Py3.ipynb | 1.28 KB | ||
| 29545018-For-Loops-Solution-Py3.ipynb | 1.8 KB | ||
| 29545028-While-Loops-and-Incrementing-Lecture-Py3.ipynb | 1.08 KB | ||
| 29545030-While-Loops-and-Incrementing-Exercise-Py3.ipynb | 1.12 KB | ||
| 29545032-While-Loops-and-Incrementing-Solution-Py3.ipynb | 1.75 KB | ||
| 29545042-Create-Lists-with-the-range-Function-Lecture-Py3.ipynb | 1.34 KB | ||
| 29545046-Create-Lists-with-the-range-Function-Exercise-Py3.ipynb | 1.45 KB | ||
| 29545048-Create-Lists-with-the-range-Function-Solution-Py3.ipynb | 2.25 KB | ||
| 29545058-Use-Conditional-Statements-and-Loops-Together-Lecture-Py3.ipynb | 1.95 KB | ||
| 29545070-Use-Conditional-Statements-and-Loops-Together-Exercise-Py3.ipynb | 2.1 KB | ||
| 29545074-Use-Conditional-Statements-and-Loops-Together-Solution-Py3.ipynb | 2.96 KB | ||
| 29545092-All-In-Lecture-Py3.ipynb | 1.62 KB | ||
| 29545100-All-In-Exercise-Py3.ipynb | 1.3 KB | ||
| 29545102-All-In-Solution-Py3.ipynb | 1.9 KB | ||
| 29545116-Iterating-over-Dictionaries-Lecture-Py3.ipynb | 1.08 KB | ||
| 29545118-Iterating-over-Dictionaries-Exercise-Py3.ipynb | 2.19 KB | ||
| 29545120-Iterating-over-Dictionaries-Solution-Py3.ipynb | 2.87 KB | ||
| 30 - Python - Advanced Python Tools | |||
| 001 Object Oriented Programming.mp4 | 8.42 MB | ||
| 001 Object Oriented Programming__en.srt | 6.1 KB | ||
| 002 Modules and Packages.mp4 | 1.71 MB | ||
| 002 Modules and Packages__en.srt | 1.34 KB | ||
| 003 What is the Standard Library_.mp4 | 4.87 MB | ||
| 003 What is the Standard Library___en.srt | 3.66 KB | ||
| 004 Importing Modules in Python.mp4 | 8.53 MB | ||
| 004 Importing Modules in Python__en.srt | 4.45 KB | ||
| 31 - Part 5_ Advanced Statistical Methods in Python | |||
| 001 Introduction to Regression Analysis.mp4 | 2.92 MB | ||
| 001 Introduction to Regression Analysis__en.srt | 2.22 KB | ||
| 22685780-Course-notes-regression-analysis.pdf | 312.18 KB | ||
| 32 - Advanced Statistical Methods - Linear Regression with StatsModels | |||
| 001 The Linear Regression Model.mp4 | 13.16 MB | ||
| 001 The Linear Regression Model__en.srt | 6.83 KB | ||
| 002 Correlation vs Regression.mp4 | 3.75 MB | ||
| 002 Correlation vs Regression__en.srt | 2.03 KB | ||
| 003 Geometrical Representation of the Linear Regression Model.mp4 | 1.75 MB | ||
| 003 Geometrical Representation of the Linear Regression Model__en.srt | 1.66 KB | ||
| 004 Python Packages Installation.mp4 | 23.7 MB | ||
| 004 Python Packages Installation__en.srt | 4.57 KB | ||
| 004 Python Packages Installation_en.vtt | 4.74 KB | ||
| 005 First Regression in Python.mp4 | 29.63 MB | ||
| 005 First Regression in Python__en.srt | 7.95 KB | ||
| 006 First Regression in Python Exercise.html | 1.31 KB | ||
| 007 Using Seaborn for Graphs.mp4 | 7.37 MB | ||
| 007 Using Seaborn for Graphs__en.srt | 1.53 KB | ||
| 008 How to Interpret the Regression Table.mp4 | 28.72 MB | ||
| 008 How to Interpret the Regression Table__en.srt | 6.57 KB | ||
| 009 Decomposition of Variability.mp4 | 8.62 MB | ||
| 009 Decomposition of Variability__en.srt | 4.2 KB | ||
| 010 What is the OLS_.mp4 | 22.44 MB | ||
| 010 What is the OLS___en.srt | 3.8 KB | ||
| 011 R-Squared.mp4 | 10.79 MB | ||
| 011 R-Squared__en.srt | 6.73 KB | ||
| 22685784-Course-notes-regression-analysis.pdf | 312.18 KB | ||
| 29587970-1.01.Simple-linear-regression.csv | 922 B | ||
| 29587976-Simple-linear-regression.ipynb | 3.79 KB | ||
| 29588016-Simple-linear-regression-with-comments.ipynb | 4.06 KB | ||
| 29588022-real-estate-price-size.csv | 1.86 KB | ||
| 29588024-Simple-Linear-Regression-Exercise-Solution.ipynb | 3.57 KB | ||
| 29588026-Simple-Linear-Regression-Exercise.ipynb | 2.78 KB | ||
| 33 - Advanced Statistical Methods - Multiple Linear Regression with StatsModels | |||
| 001 Multiple Linear Regression.mp4 | 5.54 MB | ||
| 001 Multiple Linear Regression__en.srt | 3.32 KB | ||
| 002 Adjusted R-Squared.mp4 | 34.22 MB | ||
| 002 Adjusted R-Squared__en.srt | 7.57 KB | ||
| 003 Multiple Linear Regression Exercise.html | 76 B | ||
| 004 Test for Significance of the Model (F-Test).mp4 | 5.9 MB | ||
| 004 Test for Significance of the Model (F-Test)__en.srt | 2.57 KB | ||
| 005 OLS Assumptions.mp4 | 5.12 MB | ||
| 005 OLS Assumptions__en.srt | 2.96 KB | ||
| 006 A1_ Linearity.mp4 | 2.66 MB | ||
| 006 A1_ Linearity__en.srt | 2.38 KB | ||
| 007 A2_ No Endogeneity.mp4 | 8.99 MB | ||
| 007 A2_ No Endogeneity__en.srt | 5.27 KB | ||
| 008 A3_ Normality and Homoscedasticity.mp4 | 27.39 MB | ||
| 008 A3_ Normality and Homoscedasticity__en.srt | 6.58 KB | ||
| 009 A4_ No Autocorrelation.mp4 | 7.67 MB | ||
| 009 A4_ No Autocorrelation__en.srt | 4.82 KB | ||
| 010 A5_ No Multicollinearity.mp4 | 7.36 MB | ||
| 010 A5_ No Multicollinearity__en.srt | 4.69 KB | ||
| 011 Dealing with Categorical Data - Dummy Variables.mp4 | 35.09 MB | ||
| 011 Dealing with Categorical Data - Dummy Variables__en.srt | 8.16 KB | ||
| 012 Dealing with Categorical Data - Dummy Variables.html | 76 B | ||
| 013 Making Predictions with the Linear Regression.mp4 | 16.36 MB | ||
| 013 Making Predictions with the Linear Regression__en.srt | 4.54 KB | ||
| 29588058-1.02.Multiple-linear-regression.csv | 1.09 KB | ||
| 29588064-Multiple-linear-regression-and-Adjusted-R-squared.ipynb | 2.15 KB | ||
| 29588066-Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb | 2.8 KB | ||
| 29588068-Multiple-Linear-Regression-Exercise-Solution.ipynb | 13.39 KB | ||
| 29588072-Multiple-Linear-Regression-Exercise.ipynb | 2.45 KB | ||
| 29588076-real-estate-price-size-year.csv | 2.35 KB | ||
| 29588090-1.03.Dummies.csv | 1.19 KB | ||
| 29588094-Dummy-Variables.ipynb | 4.62 KB | ||
| 29588120-Dummy-variables-with-comments.ipynb | 7.09 KB | ||
| 29588124-Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb | 18 KB | ||
| 29588128-Multiple-Linear-Regression-with-Dummies-Exercise.ipynb | 3.01 KB | ||
| 29588130-real-estate-price-size-year-view.csv | 3.39 KB | ||
| 29588138-Making-predictions.ipynb | 5.77 KB | ||
| 29588142-Making-predictions-with-comments.ipynb | 9.41 KB | ||
| 34 - Advanced Statistical Methods - Linear Regression with sklearn | |||
| 001 What is sklearn and How is it Different from Other Packages.mp4 | 6.24 MB | ||
| 001 What is sklearn and How is it Different from Other Packages__en.srt | 3.38 KB | ||
| 002 How are we Going to Approach this Section_.mp4 | 4.03 MB | ||
| 002 How are we Going to Approach this Section___en.srt | 1.56 KB | ||
| 002 How are we Going to Approach this Section__en.vtt | 2.56 KB | ||
| 003 Simple Linear Regression with sklearn.mp4 | 31.65 MB | ||
| 003 Simple Linear Regression with sklearn__en.srt | 1.06 KB | ||
| 003 Simple Linear Regression with sklearn_en.vtt | 6.71 KB | ||
| 004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 | 28.88 MB | ||
| 004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table_en.vtt | 6.08 KB | ||
| 005 A Note on Normalization.html | 729 B | ||
| 006 Simple Linear Regression with sklearn - Exercise.html | 76 B | ||
| 007 Multiple Linear Regression with sklearn.mp4 | 9.81 MB | ||
| 007 Multiple Linear Regression with sklearn__en.srt | 1013 B | ||
| 007 Multiple Linear Regression with sklearn_en.vtt | 3.8 KB | ||
| 008 Calculating the Adjusted R-Squared in sklearn.mp4 | 16.92 MB | ||
| 008 Calculating the Adjusted R-Squared in sklearn__en.srt | 6.6 KB | ||
| 009 Calculating the Adjusted R-Squared in sklearn - Exercise.html | 76 B | ||
| 010 Feature Selection (F-regression).mp4 | 15.68 MB | ||
| 010 Feature Selection (F-regression)__en.srt | 6.73 KB | ||
| 011 A Note on Calculation of P-values with sklearn.html | 370 B | ||
| 012 Creating a Summary Table with P-values.mp4 | 6.45 MB | ||
| 012 Creating a Summary Table with P-values__en.srt | 3.04 KB | ||
| 013 Multiple Linear Regression - Exercise.html | 76 B | ||
| 014 Feature Scaling (Standardization).mp4 | 20.37 MB | ||
| 014 Feature Scaling (Standardization)__en.srt | 7.79 KB | ||
| 015 Feature Selection through Standardization of Weights.mp4 | 27.16 MB | ||
| 015 Feature Selection through Standardization of Weights__en.srt | 7.47 KB | ||
| 016 Predicting with the Standardized Coefficients.mp4 | 18.34 MB | ||
| 016 Predicting with the Standardized Coefficients__en.srt | 5.81 KB | ||
| 017 Feature Scaling (Standardization) - Exercise.html | 76 B | ||
| 018 Underfitting and Overfitting.mp4 | 5.69 MB | ||
| 018 Underfitting and Overfitting__en.srt | 3.43 KB | ||
| 019 Train - Test Split Explained.mp4 | 35.58 MB | ||
| 019 Train - Test Split Explained__en.srt | 9.82 KB | ||
| 29588160-1.01.Simple-linear-regression.csv | 922 B | ||
| 29588164-sklearn-Simple-Linear-Regression.ipynb | 4.92 KB | ||
| 29588166-sklearn-Simple-Linear-Regression-with-comments.ipynb | 6.06 KB | ||
| 29588200-1.01.Simple-linear-regression.csv | 922 B | ||
| 29588206-sklearn-Simple-Linear-Regression.ipynb | 26.07 KB | ||
| 29588208-sklearn-Simple-Linear-Regression-with-comments.ipynb | 28.35 KB | ||
| 29588240-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588244-sklearn-Multiple-Linear-Regression.ipynb | 7.79 KB | ||
| 29588246-sklearn-Multiple-Linear-Regression-with-comments.ipynb | 8.65 KB | ||
| 29588306-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588310-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared.ipynb | 9.11 KB | ||
| 29588312-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-with-comments.ipynb | 10.41 KB | ||
| 29588320-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588324-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise-Solution.ipynb | 10.31 KB | ||
| 29588328-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise.ipynb | 9.83 KB | ||
| 29588334-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588340-sklearn-Feature-Selection-with-F-regression.ipynb | 10.44 KB | ||
| 29588342-sklearn-Feature-Selection-with-F-regression-with-comments.ipynb | 12.99 KB | ||
| 29588350-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588358-sklearn-How-to-properly-include-p-values.ipynb | 12.71 KB | ||
| 29588366-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588370-sklearn-Multiple-Linear-Regression-Summary-Table.ipynb | 13.71 KB | ||
| 29588372-sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb | 16.63 KB | ||
| 29588378-real-estate-price-size-year.csv | 2.35 KB | ||
| 29588380-sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb | 15.44 KB | ||
| 29588382-sklearn-Multiple-Linear-Regression-Exercise.ipynb | 5.67 KB | ||
| 29588388-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588392-sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb | 11.73 KB | ||
| 29588394-SKLEAR-1.IPY | 12.87 KB | ||
| 29588398-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588400-sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb | 14.89 KB | ||
| 29588412-SKLEAR-1.IPY | 16.79 KB | ||
| 29588414-1.02.Multiple-linear-regression.csv | 1.07 KB | ||
| 29588416-sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb | 29.75 KB | ||
| 29588422-sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb | 22.03 KB | ||
| 29588430-real-estate-price-size-year.csv | 2.35 KB | ||
| 29588432-sklearn-Feature-Scaling-Exercise-Solution.ipynb | 16.28 KB | ||
| 29588434-sklearn-Feature-Scaling-Exercise.ipynb | 6.07 KB | ||
| 29588436-sklearn-Train-Test-Split.ipynb | 7.23 KB | ||
| 29588440-sklearn-Train-Test-Split-with-comments.ipynb | 9.05 KB | ||
| 33130180-real-estate-price-size.csv | 1.86 KB | ||
| 33130182-Simple-Linear-Regression-with-sklearn-Exercise.ipynb | 4.08 KB | ||
| 33130186-Simple-Linear-Regression-with-sklearn-Exercise-Solution.ipynb | 26.61 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 35 - Advanced Statistical Methods - Practical Example_ Linear Regression | |||
| 001 Practical Example_ Linear Regression (Part 1).mp4 | 84.84 MB | ||
| 001 Practical Example_ Linear Regression (Part 1)__en.srt | 14.94 KB | ||
| 002 Practical Example_ Linear Regression (Part 2).mp4 | 31.9 MB | ||
| 002 Practical Example_ Linear Regression (Part 2)__en.srt | 5 KB | ||
| 002 Practical Example_ Linear Regression (Part 2)_en.vtt | 7.11 KB | ||
| 003 A Note on Multicollinearity.html | 849 B | ||
| 004 Practical Example_ Linear Regression (Part 3).mp4 | 6.91 MB | ||
| 004 Practical Example_ Linear Regression (Part 3)__en.srt | 4.19 KB | ||
| 005 Dummies and Variance Inflation Factor - Exercise.html | 76 B | ||
| 006 Practical Example_ Linear Regression (Part 4).mp4 | 29.84 MB | ||
| 006 Practical Example_ Linear Regression (Part 4)__en.srt | 11.75 KB | ||
| 007 Dummy Variables - Exercise.html | 705 B | ||
| 008 Practical Example_ Linear Regression (Part 5).mp4 | 50.42 MB | ||
| 008 Practical Example_ Linear Regression (Part 5)__en.srt | 10.44 KB | ||
| 009 Linear Regression - Exercise.html | 497 B | ||
| 29588446-1.04.Real-life-example.csv | 219.83 KB | ||
| 29588452-sklearn-Linear-Regression-Practical-Example-Part-1.ipynb | 166.91 KB | ||
| 29588454-sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb | 171.38 KB | ||
| 29588460-1.04.Real-life-example.csv | 219.83 KB | ||
| 29588462-sklearn-Linear-Regression-Practical-Example-Part-2.ipynb | 328.74 KB | ||
| 29588466-sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb | 335.63 KB | ||
| 29588552-sklearn-Linear-Regression-Practical-Example-Part-3.ipynb | 343.58 KB | ||
| 29588558-sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb | 351.47 KB | ||
| 29588598-1.04.Real-life-example.csv | 219.83 KB | ||
| 29588602-sklearn-Dummies-and-VIF-Exercise-Solution.ipynb | 370.22 KB | ||
| 29588604-sklearn-Dummies-and-VIF-Exercise.ipynb | 344.62 KB | ||
| 29588606-1.04.Real-life-example.csv | 219.83 KB | ||
| 29588612-sklearn-Linear-Regression-Practical-Example-Part-4.ipynb | 397.23 KB | ||
| 29588618-sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb | 407.59 KB | ||
| 29588624-1.04.Real-life-example.csv | 219.83 KB | ||
| 29588626-sklearn-Linear-Regression-Practical-Example-Part-5.ipynb | 698.36 KB | ||
| 29588630-sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb | 711.05 KB | ||
| external-assets-links.txt | 130 B | ||
| 36 - Advanced Statistical Methods - Logistic Regression | |||
| 001 Introduction to Logistic Regression.mp4 | 4.41 MB | ||
| 001 Introduction to Logistic Regression__en.srt | 1.71 KB | ||
| 002 A Simple Example in Python.mp4 | 21.91 MB | ||
| 002 A Simple Example in Python__en.srt | 5.91 KB | ||
| 003 Logistic vs Logit Function.mp4 | 43.96 MB | ||
| 003 Logistic vs Logit Function__en.srt | 4.89 KB | ||
| 004 Building a Logistic Regression.mp4 | 8.61 MB | ||
| 004 Building a Logistic Regression__en.srt | 3.43 KB | ||
| 005 Building a Logistic Regression - Exercise.html | 87 B | ||
| 006 An Invaluable Coding Tip.mp4 | 16.77 MB | ||
| 006 An Invaluable Coding Tip__en.srt | 3.15 KB | ||
| 007 Understanding Logistic Regression Tables.mp4 | 12.89 MB | ||
| 007 Understanding Logistic Regression Tables__en.srt | 5.52 KB | ||
| 008 Understanding Logistic Regression Tables - Exercise.html | 87 B | ||
| 009 What do the Odds Actually Mean.mp4 | 11.38 MB | ||
| 009 What do the Odds Actually Mean__en.srt | 5.08 KB | ||
| 010 Binary Predictors in a Logistic Regression.mp4 | 18.47 MB | ||
| 010 Binary Predictors in a Logistic Regression__en.srt | 5.7 KB | ||
| 011 Binary Predictors in a Logistic Regression - Exercise.html | 87 B | ||
| 012 Calculating the Accuracy of the Model.mp4 | 20.28 MB | ||
| 012 Calculating the Accuracy of the Model__en.srt | 4.41 KB | ||
| 013 Calculating the Accuracy of the Model.html | 87 B | ||
| 014 Underfitting and Overfitting.mp4 | 7.25 MB | ||
| 014 Underfitting and Overfitting__en.srt | 4.88 KB | ||
| 015 Testing the Model.mp4 | 21.6 MB | ||
| 015 Testing the Model__en.srt | 6.46 KB | ||
| 016 Testing the Model - Exercise.html | 87 B | ||
| 15451783-Example-bank-data.csv | 6.21 KB | ||
| 15451889-Bank-data.csv | 19.55 KB | ||
| 15451939-Bank-data.csv | 19.55 KB | ||
| 15451967-Bank-data.csv | 19.55 KB | ||
| 15452033-Bank-data.csv | 19.55 KB | ||
| 15452035-Bank-data-testing.csv | 8.3 KB | ||
| 23412976-Course-Notes-Logistic-Regression.pdf | 335.17 KB | ||
| 23413016-Course-Notes-Logistic-Regression.pdf | 335.17 KB | ||
| 29588638-2.01.Admittance.csv | 1.58 KB | ||
| 29588642-Admittance.ipynb | 3.54 KB | ||
| 29588644-Admittance-with-comments.ipynb | 5.32 KB | ||
| 29588660-Admittance-regression-tables-fixed-error.ipynb | 4.11 KB | ||
| 29588666-Admittance-regression.ipynb | 2.09 KB | ||
| 29588668-Admittance-regression-summary-error.ipynb | 2.48 KB | ||
| 29588676-Building-a-Logistic-Regression-Exercise.ipynb | 2.92 KB | ||
| 29588678-Building-a-Logistic-Regression-Solution.ipynb | 4.44 KB | ||
| 29588694-Understanding-Logistic-Regression-Tables-Exercise.ipynb | 3.16 KB | ||
| 29588700-Understanding-Logistic-Regression-Tables-Solution.ipynb | 4.79 KB | ||
| 29588712-2.02.Binary-predictors.csv | 2.56 KB | ||
| 29588716-Binary-predictors.ipynb | 2.41 KB | ||
| 29588826-Binary-Predictors-in-a-Logistic-Regression-Exercise.ipynb | 2.54 KB | ||
| 29588832-Binary-Predictors-in-a-Logistic-Regression-Solution.ipynb | 4.51 KB | ||
| 29588838-Accuracy.ipynb | 3.63 KB | ||
| 29588842-Accuracy-with-comments.ipynb | 11.67 KB | ||
| 29588854-Calculating-the-Accuracy-of-the-Model-Exercise.ipynb | 5.39 KB | ||
| 29588856-Calculating-the-Accuracy-of-the-Model-Solution.ipynb | 81.21 KB | ||
| 29588864-Testing-the-model.ipynb | 5.77 KB | ||
| 29588872-2.03.Test-dataset.csv | 322 B | ||
| 29588876-Testing-the-model-with-comments.ipynb | 7.56 KB | ||
| 29588894-Testing-the-Model-Exercise.ipynb | 6.79 KB | ||
| 29588898-Testing-the-Model-Solution.ipynb | 111.1 KB | ||
| 37 - Advanced Statistical Methods - Cluster Analysis | |||
| 001 Introduction to Cluster Analysis.mp4 | 10.66 MB | ||
| 001 Introduction to Cluster Analysis__en.srt | 4.77 KB | ||
| 002 Some Examples of Clusters.mp4 | 35.12 MB | ||
| 002 Some Examples of Clusters__en.srt | 6.2 KB | ||
| 003 Difference between Classification and Clustering.mp4 | 9.53 MB | ||
| 003 Difference between Classification and Clustering__en.srt | 3.34 KB | ||
| 004 Math Prerequisites.mp4 | 4.47 MB | ||
| 004 Math Prerequisites__en.srt | 4.18 KB | ||
| 23413656-Course-Notes-Cluster-Analysis.pdf | 208.65 KB | ||
| 23413662-Course-Notes-Cluster-Analysis.pdf | 208.65 KB | ||
| 38 - Advanced Statistical Methods - K-Means Clustering | |||
| 001 K-Means Clustering.mp4 | 10.53 MB | ||
| 001 K-Means Clustering__en.srt | 6.48 KB | ||
| 002 A Simple Example of Clustering.mp4 | 26.08 MB | ||
| 002 A Simple Example of Clustering__en.srt | 902 B | ||
| 002 A Simple Example of Clustering_en.vtt | 8.25 KB | ||
| 003 A Simple Example of Clustering - Exercise.html | 87 B | ||
| 004 Clustering Categorical Data.mp4 | 10.35 MB | ||
| 004 Clustering Categorical Data__en.srt | 3.32 KB | ||
| 005 Clustering Categorical Data - Exercise.html | 87 B | ||
| 006 How to Choose the Number of Clusters.mp4 | 19.79 MB | ||
| 006 How to Choose the Number of Clusters__en.srt | 7.41 KB | ||
| 007 How to Choose the Number of Clusters - Exercise.html | 87 B | ||
| 008 Pros and Cons of K-Means Clustering.mp4 | 10.93 MB | ||
| 008 Pros and Cons of K-Means Clustering__en.srt | 2.62 KB | ||
| 008 Pros and Cons of K-Means Clustering_en.vtt | 4.07 KB | ||
| 009 To Standardize or not to Standardize.mp4 | 10.5 MB | ||
| 009 To Standardize or not to Standardize__en.srt | 6.08 KB | ||
| 010 Relationship between Clustering and Regression.mp4 | 2.42 MB | ||
| 010 Relationship between Clustering and Regression__en.srt | 2.25 KB | ||
| 011 Market Segmentation with Cluster Analysis (Part 1).mp4 | 21.16 MB | ||
| 011 Market Segmentation with Cluster Analysis (Part 1)__en.srt | 7.32 KB | ||
| 012 Market Segmentation with Cluster Analysis (Part 2).mp4 | 34.08 MB | ||
| 012 Market Segmentation with Cluster Analysis (Part 2)__en.srt | 9.28 KB | ||
| 013 How is Clustering Useful_.mp4 | 36.49 MB | ||
| 013 How is Clustering Useful___en.srt | 6.52 KB | ||
| 014 EXERCISE_ Species Segmentation with Cluster Analysis (Part 1).html | 87 B | ||
| 015 EXERCISE_ Species Segmentation with Cluster Analysis (Part 2).html | 87 B | ||
| 15452987-Categorical.csv | 10.34 KB | ||
| 15453017-Countries-exercise.csv | 8.27 KB | ||
| 15453029-iris-dataset.csv | 2.4 KB | ||
| 15453055-iris-dataset.csv | 2.4 KB | ||
| 15453059-iris-with-answers.csv | 3.63 KB | ||
| 29588934-3.01.Country-clusters.csv | 200 B | ||
| 29588936-Country-clusters.ipynb | 3.31 KB | ||
| 29588940-Country-clusters-with-comments.ipynb | 5.8 KB | ||
| 29588950-Countries-exercise.csv | 8.27 KB | ||
| 29588952-A-Simple-Example-of-Clustering-Exercise.ipynb | 3.62 KB | ||
| 29588954-A-Simple-Example-of-Clustering-Solution.ipynb | 4.65 KB | ||
| 29588960-Categorical-data.ipynb | 3.35 KB | ||
| 29588968-Categorical-data-with-comments.ipynb | 5.62 KB | ||
| 29588982-Clustering-Categorical-Data-Exercise.ipynb | 3.78 KB | ||
| 29588986-Clustering-Categorical-Data-Solution.ipynb | 4.9 KB | ||
| 29588998-Selecting-the-number-of-clusters.ipynb | 4.53 KB | ||
| 29589000-Selecting-the-number-of-clusters-with-comments.ipynb | 7.48 KB | ||
| 29589006-How-to-Choose-the-Number-of-Clusters-Exercise.ipynb | 5.55 KB | ||
| 29589008-How-to-Choose-the-Number-of-Clusters-Solution.ipynb | 8.49 KB | ||
| 29589020-Market-segmentation-example.ipynb | 3.8 KB | ||
| 29589022-Market-segmentation-example-with-comments.ipynb | 5.9 KB | ||
| 29589028-3.12.Example.csv | 283 B | ||
| 29589036-Market-segmentation-example-Part2.ipynb | 4.68 KB | ||
| 29589038-Market-segmentation-example-Part2-with-comments.ipynb | 6.81 KB | ||
| 29589044-Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb | 4.46 KB | ||
| 29589048-Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb | 7.35 KB | ||
| 29589052-Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb | 10.74 KB | ||
| 29589056-Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb | 15.3 KB | ||
| 39 - Advanced Statistical Methods - Other Types of Clustering | |||
| 001 Types of Clustering.mp4 | 7.57 MB | ||
| 001 Types of Clustering__en.srt | 4.74 KB | ||
| 002 Dendrogram.mp4 | 17.34 MB | ||
| 002 Dendrogram__en.srt | 7.28 KB | ||
| 003 Heatmaps.mp4 | 25.71 MB | ||
| 003 Heatmaps__en.srt | 6.24 KB | ||
| 29589066-Heatmaps.ipynb | 1.82 KB | ||
| 29589070-Heatmaps-with-comments.ipynb | 17.66 KB | ||
| 29589074-Country-clusters-standardized.csv | 244 B | ||
| 40 - Part 6_ Mathematics | |||
| 001 What is a Matrix_.mp4 | 11.7 MB | ||
| 001 What is a Matrix___en.srt | 4.42 KB | ||
| 002 Scalars and Vectors.mp4 | 8.39 MB | ||
| 002 Scalars and Vectors__en.srt | 3.83 KB | ||
| 003 Linear Algebra and Geometry.mp4 | 13.56 MB | ||
| 003 Linear Algebra and Geometry__en.srt | 4.07 KB | ||
| 004 Arrays in Python - A Convenient Way To Represent Matrices.mp4 | 19.01 MB | ||
| 004 Arrays in Python - A Convenient Way To Represent Matrices__en.srt | 6.03 KB | ||
| 005 What is a Tensor_.mp4 | 11.61 MB | ||
| 005 What is a Tensor___en.srt | 3.69 KB | ||
| 006 Addition and Subtraction of Matrices.mp4 | 22.08 MB | ||
| 006 Addition and Subtraction of Matrices__en.srt | 4 KB | ||
| 007 Errors when Adding Matrices.mp4 | 3.34 MB | ||
| 007 Errors when Adding Matrices__en.srt | 2.61 KB | ||
| 008 Transpose of a Matrix.mp4 | 20.49 MB | ||
| 008 Transpose of a Matrix__en.srt | 5.71 KB | ||
| 009 Dot Product.mp4 | 11.36 MB | ||
| 009 Dot Product__en.srt | 4.32 KB | ||
| 010 Dot Product of Matrices.mp4 | 26.42 MB | ||
| 010 Dot Product of Matrices__en.srt | 9.57 KB | ||
| 011 Why is Linear Algebra Useful_.mp4 | 86.18 MB | ||
| 011 Why is Linear Algebra Useful___en.srt | 12.42 KB | ||
| 29589122-Scalars-Vectors-and-Matrices.ipynb | 4.55 KB | ||
| 29589126-Tensors.ipynb | 2.08 KB | ||
| 29589134-Adding-and-subtracting-matrices.ipynb | 3.22 KB | ||
| 29589174-Errors-when-adding-scalars-vectors-and-matrices-in-Python.ipynb | 3.17 KB | ||
| 29589180-Tranpose-of-a-matrix.ipynb | 2.89 KB | ||
| 29589188-Dot-product.ipynb | 2.13 KB | ||
| 29589194-Dot-product-Part-2.ipynb | 3.6 KB | ||
| 41 - Part 7_ Deep Learning | |||
| 001 What to Expect from this Part_.mp4 | 7.56 MB | ||
| 001 What to Expect from this Part___en.srt | 4.61 KB | ||
| 42 - Deep Learning - Introduction to Neural Networks | |||
| 001 Introduction to Neural Networks.mp4 | 10.37 MB | ||
| 001 Introduction to Neural Networks__en.srt | 6.09 KB | ||
| 002 Training the Model.mp4 | 7.57 MB | ||
| 002 Training the Model__en.srt | 4.42 KB | ||
| 003 Types of Machine Learning.mp4 | 9.81 MB | ||
| 003 Types of Machine Learning__en.srt | 5.31 KB | ||
| 004 The Linear Model (Linear Algebraic Version).mp4 | 7.87 MB | ||
| 004 The Linear Model (Linear Algebraic Version)__en.srt | 3.92 KB | ||
| 005 The Linear Model with Multiple Inputs.mp4 | 7.77 MB | ||
| 005 The Linear Model with Multiple Inputs__en.srt | 3.21 KB | ||
| 006 The Linear model with Multiple Inputs and Multiple Outputs.mp4 | 16.23 MB | ||
| 006 The Linear model with Multiple Inputs and Multiple Outputs__en.srt | 5.42 KB | ||
| 007 Graphical Representation of Simple Neural Networks.mp4 | 6.35 MB | ||
| 007 Graphical Representation of Simple Neural Networks__en.srt | 2.83 KB | ||
| 008 What is the Objective Function_.mp4 | 6.03 MB | ||
| 008 What is the Objective Function___en.srt | 2.13 KB | ||
| 009 Common Objective Functions_ L2-norm Loss.mp4 | 4.47 MB | ||
| 009 Common Objective Functions_ L2-norm Loss__en.srt | 2.76 KB | ||
| 010 Common Objective Functions_ Cross-Entropy Loss.mp4 | 9.68 MB | ||
| 010 Common Objective Functions_ Cross-Entropy Loss__en.srt | 5.63 KB | ||
| 011 Optimization Algorithm_ 1-Parameter Gradient Descent.mp4 | 22.7 MB | ||
| 011 Optimization Algorithm_ 1-Parameter Gradient Descent__en.srt | 8.75 KB | ||
| 012 Optimization Algorithm_ n-Parameter Gradient Descent.mp4 | 16.35 MB | ||
| 012 Optimization Algorithm_ n-Parameter Gradient Descent__en.srt | 7.75 KB | ||
| 16752952-Course-Notes-Section-2.pdf | 578.08 KB | ||
| 16752958-Course-Notes-Section-2.pdf | 578.08 KB | ||
| 17187788-GD-function-example.xlsx | 42.33 KB | ||
| 43 - Deep Learning - How to Build a Neural Network from Scratch with NumPy | |||
| 001 Basic NN Example (Part 1).mp4 | 5.14 MB | ||
| 001 Basic NN Example (Part 1)__en.srt | 4.52 KB | ||
| 002 Basic NN Example (Part 2).mp4 | 15.23 MB | ||
| 002 Basic NN Example (Part 2)__en.srt | 6.9 KB | ||
| 003 Basic NN Example (Part 3).mp4 | 15.68 MB | ||
| 003 Basic NN Example (Part 3)__en.srt | 4.39 KB | ||
| 004 Basic NN Example (Part 4).mp4 | 30.06 MB | ||
| 004 Basic NN Example (Part 4)__en.srt | 10.56 KB | ||
| 005 Basic NN Example Exercises.html | 1.65 KB | ||
| 13070602-Shortcuts-for-Jupyter.pdf | 619.17 KB | ||
| 29589208-Minimal-example-Part-1.ipynb | 1.19 KB | ||
| 29589218-Minimal-example-Part-2.ipynb | 3.65 KB | ||
| 29589230-Minimal-example-Part-3.ipynb | 6.79 KB | ||
| 29589236-Minimal-example-Part-4-Complete.ipynb | 11.41 KB | ||
| 29589260-Minimal-example-All-Exercises.ipynb | 12.89 KB | ||
| 29589266-Minimal-example-Exercise-1-Solution.ipynb | 69 KB | ||
| 29589272-Minimal-example-Exercise-2-Solution.ipynb | 61.41 KB | ||
| 29589274-Minimal-example-Exercise-3.a.Solution.ipynb | 67.89 KB | ||
| 29589278-Minimal-example-Exercise-3.b.Solution.ipynb | 67.72 KB | ||
| 29589280-Minimal-example-Exercise-3.c.Solution.ipynb | 70.13 KB | ||
| 29589288-Minimal-example-Exercise-3.d.Solution.ipynb | 84.13 KB | ||
| 29589294-Minimal-example-Exercise-4-Solution.ipynb | 66.52 KB | ||
| 29589298-Minimal-example-Exercise-5-Solution.ipynb | 68.88 KB | ||
| 29589302-Minimal-example-Exercise-6.ipynb | 61.76 KB | ||
| 29589304-Minimal-example-Exercise-6-Solution.ipynb | 61.76 KB | ||
| 44 - Deep Learning - TensorFlow 2.0_ Introduction | |||
| 001 How to Install TensorFlow 2.0.mp4 | 27.34 MB | ||
| 001 How to Install TensorFlow 2.0__en.srt | 6.52 KB | ||
| 002 TensorFlow Outline and Comparison with Other Libraries.mp4 | 14.94 MB | ||
| 002 TensorFlow Outline and Comparison with Other Libraries__en.srt | 1.5 KB | ||
| 002 TensorFlow Outline and Comparison with Other Libraries_en.vtt | 4.74 KB | ||
| 003 TensorFlow 1 vs TensorFlow 2.mp4 | 14.95 MB | ||
| 003 TensorFlow 1 vs TensorFlow 2__en.srt | 3.76 KB | ||
| 004 A Note on TensorFlow 2 Syntax.mp4 | 2.34 MB | ||
| 004 A Note on TensorFlow 2 Syntax__en.srt | 1.41 KB | ||
| 005 Types of File Formats Supporting TensorFlow.mp4 | 7.25 MB | ||
| 005 Types of File Formats Supporting TensorFlow__en.srt | 3.56 KB | ||
| 006 Outlining the Model with TensorFlow 2.mp4 | 26.99 MB | ||
| 006 Outlining the Model with TensorFlow 2__en.srt | 7.99 KB | ||
| 007 Interpreting the Result and Extracting the Weights and Bias.mp4 | 13.67 MB | ||
| 007 Interpreting the Result and Extracting the Weights and Bias__en.srt | 6.26 KB | ||
| 008 Customizing a TensorFlow 2 Model.mp4 | 16.78 MB | ||
| 008 Customizing a TensorFlow 2 Model__en.srt | 4.2 KB | ||
| 009 Basic NN with TensorFlow_ Exercises.html | 1.28 KB | ||
| 13070604-Shortcuts-for-Jupyter.pdf | 619.17 KB | ||
| 29589774-TensorFlow-Minimal-example-Part1.ipynb | 1.66 KB | ||
| 29589782-TensorFlow-Minimal-example-Part2.ipynb | 9.06 KB | ||
| 29589788-TensorFlow-Minimal-example-Part3.ipynb | 76.52 KB | ||
| 29589804-TensorFlow-Minimal-example-complete.ipynb | 76.85 KB | ||
| 29589808-TensorFlow-Minimal-example-complete-with-comments.ipynb | 82.29 KB | ||
| 29589822-TensorFlow-Minimal-example-All-exercises.ipynb | 83.62 KB | ||
| 29589824-TensorFlow-Minimal-example-Exercise-1-Solution.ipynb | 27.96 KB | ||
| 29589828-TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb | 83.68 KB | ||
| 29589834-TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb | 77.52 KB | ||
| 29589836-TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb | 84.44 KB | ||
| 45 - Deep Learning - Digging Deeper into NNs_ Introducing Deep Neural Networks | |||
| 001 What is a Layer_.mp4 | 3.47 MB | ||
| 001 What is a Layer___en.srt | 2.44 KB | ||
| 002 What is a Deep Net_.mp4 | 11.06 MB | ||
| 002 What is a Deep Net___en.srt | 3.3 KB | ||
| 003 Digging into a Deep Net.mp4 | 19.14 MB | ||
| 003 Digging into a Deep Net__en.srt | 6.73 KB | ||
| 004 Non-Linearities and their Purpose.mp4 | 9.74 MB | ||
| 004 Non-Linearities and their Purpose__en.srt | 3.8 KB | ||
| 005 Activation Functions.mp4 | 8.53 MB | ||
| 005 Activation Functions__en.srt | 5.33 KB | ||
| 006 Activation Functions_ Softmax Activation.mp4 | 8.42 MB | ||
| 006 Activation Functions_ Softmax Activation__en.srt | 4.51 KB | ||
| 007 Backpropagation.mp4 | 19.49 MB | ||
| 007 Backpropagation__en.srt | 4.48 KB | ||
| 008 Backpropagation Picture.mp4 | 7.68 MB | ||
| 008 Backpropagation Picture__en.srt | 4.27 KB | ||
| 009 Backpropagation - A Peek into the Mathematics of Optimization.html | 539 B | ||
| 13070016-Course-Notes-Section-6.pdf | 936.42 KB | ||
| 13070018-Course-Notes-Section-6.pdf | 936.42 KB | ||
| 21993772-Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf | 182.38 KB | ||
| 46 - Deep Learning - Overfitting | |||
| 001 What is Overfitting_.mp4 | 10.5 MB | ||
| 001 What is Overfitting___en.srt | 5.73 KB | ||
| 002 Underfitting and Overfitting for Classification.mp4 | 13.53 MB | ||
| 002 Underfitting and Overfitting for Classification__en.srt | 2.69 KB | ||
| 003 What is Validation_.mp4 | 8.14 MB | ||
| 003 What is Validation___en.srt | 4.9 KB | ||
| 004 Training, Validation, and Test Datasets.mp4 | 7.74 MB | ||
| 004 Training, Validation, and Test Datasets__en.srt | 3.41 KB | ||
| 005 N-Fold Cross Validation.mp4 | 5.14 MB | ||
| 005 N-Fold Cross Validation__en.srt | 4.29 KB | ||
| 006 Early Stopping or When to Stop Training.mp4 | 8.5 MB | ||
| 006 Early Stopping or When to Stop Training__en.srt | 6.79 KB | ||
| 47 - Deep Learning - Initialization | |||
| 001 What is Initialization_.mp4 | 17.42 MB | ||
| 001 What is Initialization___en.srt | 3.6 KB | ||
| 002 Types of Simple Initializations.mp4 | 5.73 MB | ||
| 002 Types of Simple Initializations__en.srt | 3.82 KB | ||
| 003 State-of-the-Art Method - (Xavier) Glorot Initialization.mp4 | 4.18 MB | ||
| 003 State-of-the-Art Method - (Xavier) Glorot Initialization__en.srt | 3.67 KB | ||
| 48 - Deep Learning - Digging into Gradient Descent and Learning Rate Schedules | |||
| 001 Stochastic Gradient Descent.mp4 | 7.62 MB | ||
| 001 Stochastic Gradient Descent__en.srt | 4.74 KB | ||
| 002 Problems with Gradient Descent.mp4 | 3.51 MB | ||
| 002 Problems with Gradient Descent__en.srt | 2.92 KB | ||
| 003 Momentum.mp4 | 5.01 MB | ||
| 003 Momentum__en.srt | 3.59 KB | ||
| 004 Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4 | 12.03 MB | ||
| 004 Learning Rate Schedules, or How to Choose the Optimal Learning Rate__en.srt | 6.12 KB | ||
| 005 Learning Rate Schedules Visualized.mp4 | 2.34 MB | ||
| 005 Learning Rate Schedules Visualized__en.srt | 2.14 KB | ||
| 006 Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4 | 8.24 MB | ||
| 006 Adaptive Learning Rate Schedules (AdaGrad and RMSprop )__en.srt | 5.22 KB | ||
| 007 Adam (Adaptive Moment Estimation).mp4 | 6.88 MB | ||
| 007 Adam (Adaptive Moment Estimation)__en.srt | 3.42 KB | ||
| 49 - Deep Learning - Preprocessing | |||
| 001 Preprocessing Introduction.mp4 | 8.98 MB | ||
| 001 Preprocessing Introduction__en.srt | 3.81 KB | ||
| 002 Types of Basic Preprocessing.mp4 | 2.4 MB | ||
| 002 Types of Basic Preprocessing__en.srt | 1.72 KB | ||
| 003 Standardization.mp4 | 11.95 MB | ||
| 003 Standardization__en.srt | 6.2 KB | ||
| 004 Preprocessing Categorical Data.mp4 | 5.34 MB | ||
| 004 Preprocessing Categorical Data__en.srt | 2.86 KB | ||
| 005 Binary and One-Hot Encoding.mp4 | 8.36 MB | ||
| 005 Binary and One-Hot Encoding__en.srt | 4.78 KB | ||
| 50 - Deep Learning - Classifying on the MNIST Dataset | |||
| 001 MNIST_ The Dataset.mp4 | 4.06 MB | ||
| 001 MNIST_ The Dataset__en.srt | 3.48 KB | ||
| 002 MNIST_ How to Tackle the MNIST.mp4 | 7.66 MB | ||
| 002 MNIST_ How to Tackle the MNIST__en.srt | 3.78 KB | ||
| 003 MNIST_ Importing the Relevant Packages and Loading the Data.mp4 | 12.24 MB | ||
| 003 MNIST_ Importing the Relevant Packages and Loading the Data__en.srt | 3.01 KB | ||
| 004 MNIST_ Preprocess the Data - Create a Validation Set and Scale It.mp4 | 22.93 MB | ||
| 004 MNIST_ Preprocess the Data - Create a Validation Set and Scale It__en.srt | 6.61 KB | ||
| 005 MNIST_ Preprocess the Data - Scale the Test Data - Exercise.html | 79 B | ||
| 006 MNIST_ Preprocess the Data - Shuffle and Batch.mp4 | 32.71 MB | ||
| 006 MNIST_ Preprocess the Data - Shuffle and Batch__en.srt | 9.49 KB | ||
| 007 MNIST_ Preprocess the Data - Shuffle and Batch - Exercise.html | 79 B | ||
| 008 MNIST_ Outline the Model.mp4 | 22.09 MB | ||
| 008 MNIST_ Outline the Model__en.srt | 7.26 KB | ||
| 009 MNIST_ Select the Loss and the Optimizer.mp4 | 10.65 MB | ||
| 009 MNIST_ Select the Loss and the Optimizer__en.srt | 3.18 KB | ||
| 010 MNIST_ Learning.mp4 | 31.03 MB | ||
| 010 MNIST_ Learning__en.srt | 7.87 KB | ||
| 011 MNIST - Exercises.html | 1.98 KB | ||
| 012 MNIST_ Testing the Model.mp4 | 22.64 MB | ||
| 012 MNIST_ Testing the Model__en.srt | 6.07 KB | ||
| 29589868-TensorFlow-MNIST-Part1-with-comments.ipynb | 3.97 KB | ||
| 29589876-TensorFlow-MNIST-Part2-with-comments.ipynb | 6.39 KB | ||
| 29589878-TensorFlow-MNIST-Part3-with-comments.ipynb | 8.61 KB | ||
| 29589884-TensorFlow-MNIST-Part4-with-comments.ipynb | 10.49 KB | ||
| 29589888-TensorFlow-MNIST-Part5-with-comments.ipynb | 10.99 KB | ||
| 29589892-TensorFlow-MNIST-Part6-with-comments.ipynb | 12.54 KB | ||
| 29589896-1.TensorFlow-MNIST-Width-Solution.ipynb | 14.84 KB | ||
| 29589904-2.TensorFlow-MNIST-Depth-Solution.ipynb | 15.31 KB | ||
| 29589908-3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb | 15.3 KB | ||
| 29589912-4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb | 15.11 KB | ||
| 29589920-5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb | 14.74 KB | ||
| 29589928-6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb | 15.12 KB | ||
| 29589932-7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb | 15.18 KB | ||
| 29589934-8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb | 20.58 KB | ||
| 29589940-9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb | 15.8 KB | ||
| 29589948-TensorFlow-MNIST-All-Exercises.ipynb | 16.65 KB | ||
| 29589952-TensorFlow-MNIST-around-98-percent-accuracy.ipynb | 15.02 KB | ||
| 29589956-TensorFlow-MNIST-complete.ipynb | 6.78 KB | ||
| 29589960-TensorFlow-MNIST-complete-with-comments.ipynb | 14.51 KB | ||
| 51 - Deep Learning - Business Case Example | |||
| 001 Business Case_ Exploring the Dataset and Identifying Predictors.mp4 | 51.38 MB | ||
| 001 Business Case_ Exploring the Dataset and Identifying Predictors__en.srt | 10.5 KB | ||
| 002 Business Case_ Outlining the Solution.mp4 | 2.21 MB | ||
| 002 Business Case_ Outlining the Solution__en.srt | 1.93 KB | ||
| 003 Business Case_ Balancing the Dataset.mp4 | 26.19 MB | ||
| 003 Business Case_ Balancing the Dataset__en.srt | 4.72 KB | ||
| 004 Business Case_ Preprocessing the Data.mp4 | 73.82 MB | ||
| 004 Business Case_ Preprocessing the Data__en.srt | 348 B | ||
| 004 Business Case_ Preprocessing the Data_en.vtt | 11.73 KB | ||
| 005 Business Case_ Preprocessing the Data - Exercise.html | 370 B | ||
| 006 Business Case_ Load the Preprocessed Data.mp4 | 13.8 MB | ||
| 006 Business Case_ Load the Preprocessed Data__en.srt | 4.83 KB | ||
| 007 Business Case_ Load the Preprocessed Data - Exercise.html | 79 B | ||
| 008 Business Case_ Learning and Interpreting the Result.mp4 | 27.77 MB | ||
| 008 Business Case_ Learning and Interpreting the Result__en.srt | 6.28 KB | ||
| 009 Business Case_ Setting an Early Stopping Mechanism.mp4 | 43.81 MB | ||
| 009 Business Case_ Setting an Early Stopping Mechanism__en.srt | 7.93 KB | ||
| 010 Setting an Early Stopping Mechanism - Exercise.html | 192 B | ||
| 011 Business Case_ Testing the Model.mp4 | 8.19 MB | ||
| 011 Business Case_ Testing the Model__en.srt | 2.21 KB | ||
| 012 Business Case_ Final Exercise.html | 433 B | ||
| 19664156-Audiobooks-data.csv | 710.77 KB | ||
| 29589970-TensorFlow-Audiobooks-Preprocessing.ipynb | 5.58 KB | ||
| 29589978-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb | 11.19 KB | ||
| 29589984-TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb | 8.6 KB | ||
| 29589992-TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb | 10.04 KB | ||
| 29590000-TensorFlow-Audiobooks-Machine-Learning-Part1-with-comments.ipynb | 4.61 KB | ||
| 29590002-TensorFlow-Audiobooks-Machine-Learning-Part2-with-comments.ipynb | 19.69 KB | ||
| 29590006-TensorFlow-Audiobooks-Machine-Learning-Part3-with-comments.ipynb | 10.06 KB | ||
| 29590012-TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb | 11.95 KB | ||
| 29590020-TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb | 11.95 KB | ||
| 52 - Deep Learning - Conclusion | |||
| 001 Summary on What You've Learned.mp4 | 9.66 MB | ||
| 001 Summary on What You've Learned__en.srt | 5.25 KB | ||
| 002 What's Further out there in terms of Machine Learning.mp4 | 3.71 MB | ||
| 002 What's Further out there in terms of Machine Learning__en.srt | 2.64 KB | ||
| 003 DeepMind and Deep Learning.html | 1.04 KB | ||
| 004 An overview of CNNs.mp4 | 30.47 MB | ||
| 004 An overview of CNNs__en.srt | 6.71 KB | ||
| 005 An Overview of RNNs.mp4 | 6.75 MB | ||
| 005 An Overview of RNNs__en.srt | 3.77 KB | ||
| 006 An Overview of non-NN Approaches.mp4 | 15.65 MB | ||
| 006 An Overview of non-NN Approaches__en.srt | 5.28 KB | ||
| 53 - Appendix_ Deep Learning - TensorFlow 1_ Introduction | |||
| 001 READ ME____.html | 564 B | ||
| 002 How to Install TensorFlow 1.mp4 | 3.71 MB | ||
| 002 How to Install TensorFlow 1__en.srt | 2.7 KB | ||
| 002 How to Install TensorFlow 1_en.vtt | 2.91 KB | ||
| 003 A Note on Installing Packages in Anaconda.html | 2.28 KB | ||
| 004 TensorFlow Intro.mp4 | 16.56 MB | ||
| 004 TensorFlow Intro__en.srt | 1.37 KB | ||
| 004 TensorFlow Intro_en.vtt | 4.61 KB | ||
| 005 Actual Introduction to TensorFlow.mp4 | 6.17 MB | ||
| 005 Actual Introduction to TensorFlow__en.srt | 2.29 KB | ||
| 006 Types of File Formats, supporting Tensors.mp4 | 8.9 MB | ||
| 006 Types of File Formats, supporting Tensors__en.srt | 3.3 KB | ||
| 007 Basic NN Example with TF_ Inputs, Outputs, Targets, Weights, Biases.mp4 | 28 MB | ||
| 007 Basic NN Example with TF_ Inputs, Outputs, Targets, Weights, Biases__en.srt | 7.56 KB | ||
| 008 Basic NN Example with TF_ Loss Function and Gradient Descent.mp4 | 15.72 MB | ||
| 008 Basic NN Example with TF_ Loss Function and Gradient Descent__en.srt | 4.77 KB | ||
| 009 Basic NN Example with TF_ Model Output.mp4 | 17.09 MB | ||
| 009 Basic NN Example with TF_ Model Output__en.srt | 7.7 KB | ||
| 010 Basic NN Example with TF Exercises.html | 1.58 KB | ||
| 13070608-Shortcuts-for-Jupyter.pdf | 619.17 KB | ||
| 29590038-5.3.TensorFlow-Minimal-example-Part-1.ipynb | 3.36 KB | ||
| 29590046-5.4.TensorFlow-Minimal-example-Part-2.ipynb | 6.17 KB | ||
| 29591380-5.5.TensorFlow-Minimal-example-Part-3.ipynb | 8.65 KB | ||
| 29591408-5.6.TensorFlow-Minimal-example-complete.ipynb | 12.15 KB | ||
| 29591428-TensorFlow-Minimal-Example-All-Exercises.ipynb | 13.97 KB | ||
| 29591432-TensorFlow-Minimal-Example-Exercise-1-Solution.ipynb | 23.63 KB | ||
| 29591442-TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb | 25.54 KB | ||
| 29591444-TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb | 25.51 KB | ||
| 29591454-TensorFlow-Minimal-Example-Exercise-2-3-Solution.ipynb | 49.96 KB | ||
| 29591458-TensorFlow-Minimal-Example-Exercise-2-4-Solution.ipynb | 21.75 KB | ||
| 29591464-TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb | 26.71 KB | ||
| 29591468-TensorFlow-Minimal-Example-Exercise-4-Solution.ipynb | 26.98 KB | ||
| 54 - Appendix_ Deep Learning - TensorFlow 1_ Classifying on the MNIST Dataset | |||
| 001 MNIST_ What is the MNIST Dataset_.mp4 | 4.23 MB | ||
| 001 MNIST_ What is the MNIST Dataset___en.srt | 3.52 KB | ||
| 002 MNIST_ How to Tackle the MNIST.mp4 | 7.68 MB | ||
| 002 MNIST_ How to Tackle the MNIST__en.srt | 3.72 KB | ||
| 003 MNIST_ Relevant Packages.mp4 | 7.88 MB | ||
| 003 MNIST_ Relevant Packages__en.srt | 2.25 KB | ||
| 004 MNIST_ Model Outline.mp4 | 34.69 MB | ||
| 004 MNIST_ Model Outline__en.srt | 8.95 KB | ||
| 005 MNIST_ Loss and Optimization Algorithm.mp4 | 11.56 MB | ||
| 005 MNIST_ Loss and Optimization Algorithm__en.srt | 3.6 KB | ||
| 006 Calculating the Accuracy of the Model.mp4 | 16.64 MB | ||
| 006 Calculating the Accuracy of the Model__en.srt | 5.34 KB | ||
| 007 MNIST_ Batching and Early Stopping.mp4 | 8.7 MB | ||
| 007 MNIST_ Batching and Early Stopping__en.srt | 2.83 KB | ||
| 008 MNIST_ Learning.mp4 | 31.88 MB | ||
| 008 MNIST_ Learning__en.srt | 9.95 KB | ||
| 009 MNIST_ Results and Testing.mp4 | 38.19 MB | ||
| 009 MNIST_ Results and Testing__en.srt | 8.33 KB | ||
| 010 MNIST_ Exercises.html | 2.16 KB | ||
| 011 MNIST_ Solutions.html | 2.22 KB | ||
| 29591484-12.3.TensorFlow-MNIST-with-comments-Part-1.ipynb | 3.89 KB | ||
| 29591494-12.4.TensorFlow-MNIST-with-comments-Part-2.ipynb | 6.1 KB | ||
| 29591504-12.5.TensorFlow-MNIST-with-comments-Part-3.ipynb | 7.31 KB | ||
| 29591514-12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb | 7.9 KB | ||
| 29591520-12.7.TensorFlow-MNIST-with-comments-Part-5.ipynb | 8.53 KB | ||
| 29591538-12.8.TensorFlow-MNIST-with-comments-Part-6.ipynb | 11.5 KB | ||
| 29591550-12.9.TensorFlow-MNIST-with-comments.ipynb | 13.03 KB | ||
| 29591622-TensorFlow-MNIST-Exercises-All.ipynb | 15.47 KB | ||
| 29591632-0.TensorFlow-MNIST-take-note-of-time-Solution.ipynb | 14 KB | ||
| 29591642-1.TensorFlow-MNIST-Width-Solution.ipynb | 14.01 KB | ||
| 29591650-2.TensorFlow-MNIST-Depth-Solution.ipynb | 14.87 KB | ||
| 29591654-3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb | 16.81 KB | ||
| 29591658-4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb | 14.35 KB | ||
| 29591660-5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb | 13.93 KB | ||
| 29591668-6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb | 14.26 KB | ||
| 29591682-7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb | 14.16 KB | ||
| 29591686-8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb | 14.07 KB | ||
| 29591690-9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb | 15.21 KB | ||
| 29591694-TensorFlow-MNIST-around-98-percent-accuracy.ipynb | 17.66 KB | ||
| 55 - Appendix_ Deep Learning - TensorFlow 1_ Business Case | |||
| 001 Business Case_ Getting Acquainted with the Dataset.mp4 | 60.26 MB | ||
| 001 Business Case_ Getting Acquainted with the Dataset__en.srt | 10.62 KB | ||
| 002 Business Case_ Outlining the Solution.mp4 | 2.89 MB | ||
| 002 Business Case_ Outlining the Solution__en.srt | 2.5 KB | ||
| 003 The Importance of Working with a Balanced Dataset.mp4 | 21.6 MB | ||
| 003 The Importance of Working with a Balanced Dataset__en.srt | 4.72 KB | ||
| 004 Business Case_ Preprocessing.mp4 | 74.39 MB | ||
| 004 Business Case_ Preprocessing__en.srt | 348 B | ||
| 004 Business Case_ Preprocessing_en.vtt | 11.75 KB | ||
| 005 Business Case_ Preprocessing Exercise.html | 379 B | ||
| 006 Creating a Data Provider.mp4 | 56.23 MB | ||
| 006 Creating a Data Provider__en.srt | 7.77 KB | ||
| 007 Business Case_ Model Outline.mp4 | 42.48 MB | ||
| 007 Business Case_ Model Outline__en.srt | 7.09 KB | ||
| 008 Business Case_ Optimization.mp4 | 26.95 MB | ||
| 008 Business Case_ Optimization__en.srt | 6.46 KB | ||
| 009 Business Case_ Interpretation.mp4 | 18.59 MB | ||
| 009 Business Case_ Interpretation__en.srt | 2.91 KB | ||
| 010 Business Case_ Testing the Model.mp4 | 4.39 MB | ||
| 010 Business Case_ Testing the Model__en.srt | 2.7 KB | ||
| 011 Business Case_ A Comment on the Homework.mp4 | 19.64 MB | ||
| 011 Business Case_ A Comment on the Homework__en.srt | 4.81 KB | ||
| 011 Business Case_ A Comment on the Homework_en.vtt | 4.64 KB | ||
| 012 Business Case_ Final Exercise.html | 441 B | ||
| 13070978-Audiobooks-data.csv | 710.77 KB | ||
| 29591716-Audiobooks-data.csv | 710.77 KB | ||
| 29591732-Audiobooks-data.csv | 710.77 KB | ||
| 29591734-TensorFlow-Audiobooks-Preprocessing.ipynb | 5.58 KB | ||
| 29591738-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb | 11.19 KB | ||
| 29591808-Audiobooks-data.csv | 710.77 KB | ||
| 29591812-TensorFlow-Audiobooks-Machine-learning-Homework.ipynb | 14.4 KB | ||
| 29591820-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb | 11.19 KB | ||
| 29591842-Audiobooks-data.csv | 710.77 KB | ||
| 29591844-TensorFlow-Audiobooks-Machine-learning-Homework.ipynb | 14.4 KB | ||
| 29591846-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb | 11.19 KB | ||
| 29591888-TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb | 10.64 KB | ||
| 29591892-TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb | 12.73 KB | ||
| 29591894-TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb | 10.64 KB | ||
| 29591900-TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb | 12.73 KB | ||
| 29591906-TensorFlow-Audiobooks-Outlining-the-model.ipynb | 9.36 KB | ||
| 29591910-TensorFlow-Audiobooks-Outlining-the-model-with-comments.ipynb | 10.34 KB | ||
| 29591940-Audiobooks-data.csv | 710.77 KB | ||
| 29591944-TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb | 8.6 KB | ||
| 29591948-TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb | 10.03 KB | ||
| 56 - Software Integration | |||
| 001 What are Data, Servers, Clients, Requests, and Responses.mp4 | 19.17 MB | ||
| 001 What are Data, Servers, Clients, Requests, and Responses__en.srt | 5.92 KB | ||
| 002 What are Data Connectivity, APIs, and Endpoints_.mp4 | 58.83 MB | ||
| 002 What are Data Connectivity, APIs, and Endpoints___en.srt | 8.51 KB | ||
| 003 Taking a Closer Look at APIs.mp4 | 65.29 MB | ||
| 003 Taking a Closer Look at APIs__en.srt | 10.6 KB | ||
| 004 Communication between Software Products through Text Files.mp4 | 9.28 MB | ||
| 004 Communication between Software Products through Text Files__en.srt | 5.51 KB | ||
| 005 Software Integration - Explained.mp4 | 41.99 MB | ||
| 005 Software Integration - Explained__en.srt | 6.85 KB | ||
| 57 - Case Study - What's Next in the Course_ | |||
| 001 Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 | 15.8 MB | ||
| 001 Game Plan for this Python, SQL, and Tableau Business Exercise__en.srt | 5.54 KB | ||
| 002 The Business Task.mp4 | 6.8 MB | ||
| 002 The Business Task__en.srt | 3.72 KB | ||
| 003 Introducing the Data Set.mp4 | 15.29 MB | ||
| 003 Introducing the Data Set__en.srt | 4.13 KB | ||
| 58 - Case Study - Preprocessing the 'Absenteeism_data' | |||
| 001 What to Expect from the Following Sections_.html | 2.43 KB | ||
| 002 Importing the Absenteeism Data in Python.mp4 | 18.03 MB | ||
| 002 Importing the Absenteeism Data in Python__en.srt | 3.89 KB | ||
| 003 Checking the Content of the Data Set.mp4 | 54.27 MB | ||
| 003 Checking the Content of the Data Set__en.srt | 7.12 KB | ||
| 004 Introduction to Terms with Multiple Meanings.mp4 | 18.04 MB | ||
| 004 Introduction to Terms with Multiple Meanings__en.srt | 4.09 KB | ||
| 005 What's Regression Analysis - a Quick Refresher.html | 2.8 KB | ||
| 006 Using a Statistical Approach towards the Solution to the Exercise.mp4 | 9.9 MB | ||
| 006 Using a Statistical Approach towards the Solution to the Exercise__en.srt | 2.93 KB | ||
| 007 Dropping a Column from a DataFrame in Python.mp4 | 41.3 MB | ||
| 007 Dropping a Column from a DataFrame in Python__en.srt | 7.75 KB | ||
| 008 EXERCISE - Dropping a Column from a DataFrame in Python.html | 864 B | ||
| 009 SOLUTION - Dropping a Column from a DataFrame in Python.html | 114 B | ||
| 010 Analyzing the Reasons for Absence.mp4 | 27.63 MB | ||
| 010 Analyzing the Reasons for Absence__en.srt | 6.18 KB | ||
| 011 Obtaining Dummies from a Single Feature.mp4 | 63.77 MB | ||
| 011 Obtaining Dummies from a Single Feature__en.srt | 10.28 KB | ||
| 012 EXERCISE - Obtaining Dummies from a Single Feature.html | 123 B | ||
| 013 SOLUTION - Obtaining Dummies from a Single Feature.html | 117 B | ||
| 014 Dropping a Dummy Variable from the Data Set.html | 2.31 KB | ||
| 015 More on Dummy Variables_ A Statistical Perspective.mp4 | 3.18 MB | ||
| 015 More on Dummy Variables_ A Statistical Perspective__en.srt | 1.74 KB | ||
| 016 Classifying the Various Reasons for Absence.mp4 | 51.32 MB | ||
| 016 Classifying the Various Reasons for Absence__en.srt | 10.05 KB | ||
| 017 Using .concat() in Python.mp4 | 19.77 MB | ||
| 017 Using .concat() in Python__en.srt | 5.23 KB | ||
| 018 EXERCISE - Using .concat() in Python.html | 189 B | ||
| 019 SOLUTION - Using .concat() in Python.html | 143 B | ||
| 020 Reordering Columns in a Pandas DataFrame in Python.mp4 | 7.18 MB | ||
| 020 Reordering Columns in a Pandas DataFrame in Python__en.srt | 1.87 KB | ||
| 021 EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html | 161 B | ||
| 022 SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html | 478 B | ||
| 023 Creating Checkpoints while Coding in Jupyter.mp4 | 17.34 MB | ||
| 023 Creating Checkpoints while Coding in Jupyter__en.srt | 3.72 KB | ||
| 024 EXERCISE - Creating Checkpoints while Coding in Jupyter.html | 137 B | ||
| 025 SOLUTION - Creating Checkpoints while Coding in Jupyter.html | 118 B | ||
| 026 Analyzing the Dates from the Initial Data Set.mp4 | 40.13 MB | ||
| 026 Analyzing the Dates from the Initial Data Set__en.srt | 8.55 KB | ||
| 027 Extracting the Month Value from the _Date_ Column.mp4 | 38.91 MB | ||
| 027 Extracting the Month Value from the _Date_ Column__en.srt | 7.93 KB | ||
| 028 Extracting the Day of the Week from the _Date_ Column.mp4 | 9.12 MB | ||
| 028 Extracting the Day of the Week from the _Date_ Column__en.srt | 4.4 KB | ||
| 029 EXERCISE - Removing the _Date_ Column.html | 1.14 KB | ||
| 030 Analyzing Several _Straightforward_ Columns for this Exercise.mp4 | 12.23 MB | ||
| 030 Analyzing Several _Straightforward_ Columns for this Exercise__en.srt | 4.43 KB | ||
| 031 Working on _Education_, _Children_, and _Pets_.mp4 | 19.69 MB | ||
| 031 Working on _Education_, _Children_, and _Pets___en.srt | 5.65 KB | ||
| 032 Final Remarks of this Section.mp4 | 17.04 MB | ||
| 032 Final Remarks of this Section__en.srt | 2.52 KB | ||
| 033 A Note on Exporting Your Data as a _.csv File.html | 880 B | ||
| 15271310-Absenteeism-data.csv | 32.05 KB | ||
| 15271322-data-preprocessing-homework.pdf | 134.47 KB | ||
| 15271330-df-preprocessed.csv | 29.11 KB | ||
| 29545298-Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb | 4.82 KB | ||
| 29545314-Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb | 7.33 KB | ||
| 29545316-Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb | 8.33 KB | ||
| 29545318-Absenteeism-Exercise-Preprocessing-LECTURES.ipynb | 7.6 MB | ||
| 29545334-Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb | 8.51 KB | ||
| 29545338-Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb | 4.13 KB | ||
| 59 - Case Study - Applying Machine Learning to Create the 'absenteeism_module' | |||
| 001 Exploring the Problem with a Machine Learning Mindset.mp4 | 11.08 MB | ||
| 001 Exploring the Problem with a Machine Learning Mindset__en.srt | 4.63 KB | ||
| 002 Creating the Targets for the Logistic Regression.mp4 | 32.5 MB | ||
| 002 Creating the Targets for the Logistic Regression__en.srt | 8.56 KB | ||
| 003 Selecting the Inputs for the Logistic Regression.mp4 | 4.64 MB | ||
| 003 Selecting the Inputs for the Logistic Regression__en.srt | 3.42 KB | ||
| 004 Standardizing the Data.mp4 | 15.14 MB | ||
| 004 Standardizing the Data__en.srt | 4.16 KB | ||
| 005 Splitting the Data for Training and Testing.mp4 | 36.12 MB | ||
| 005 Splitting the Data for Training and Testing__en.srt | 8.47 KB | ||
| 006 Fitting the Model and Assessing its Accuracy.mp4 | 35.29 MB | ||
| 006 Fitting the Model and Assessing its Accuracy__en.srt | 1.36 KB | ||
| 006 Fitting the Model and Assessing its Accuracy_en.vtt | 6.35 KB | ||
| 007 Creating a Summary Table with the Coefficients and Intercept.mp4 | 26.98 MB | ||
| 007 Creating a Summary Table with the Coefficients and Intercept__en.srt | 6.66 KB | ||
| 008 Interpreting the Coefficients for Our Problem.mp4 | 34.41 MB | ||
| 008 Interpreting the Coefficients for Our Problem__en.srt | 8.04 KB | ||
| 009 Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4 | 28.02 MB | ||
| 009 Standardizing only the Numerical Variables (Creating a Custom Scaler)__en.srt | 4.98 KB | ||
| 010 Interpreting the Coefficients of the Logistic Regression.mp4 | 15.22 MB | ||
| 010 Interpreting the Coefficients of the Logistic Regression__en.srt | 7.3 KB | ||
| 011 Backward Elimination or How to Simplify Your Model.mp4 | 31.96 MB | ||
| 011 Backward Elimination or How to Simplify Your Model__en.srt | 925 B | ||
| 011 Backward Elimination or How to Simplify Your Model_en.vtt | 4.58 KB | ||
| 012 Testing the Model We Created.mp4 | 31.63 MB | ||
| 012 Testing the Model We Created__en.srt | 6.51 KB | ||
| 013 Saving the Model and Preparing it for Deployment.mp4 | 25.52 MB | ||
| 013 Saving the Model and Preparing it for Deployment__en.srt | 1.23 KB | ||
| 013 Saving the Model and Preparing it for Deployment_en.vtt | 4.96 KB | ||
| 014 ARTICLE - A Note on 'pickling'.html | 2.11 KB | ||
| 015 EXERCISE - Saving the Model (and Scaler).html | 284 B | ||
| 016 Preparing the Deployment of the Model through a Module.mp4 | 28.57 MB | ||
| 016 Preparing the Deployment of the Model through a Module__en.srt | 5.51 KB | ||
| 15364076-Absenteeism-preprocessed.csv | 29.13 KB | ||
| external-assets-links.txt | 774 B | ||
| 60 - Case Study - Loading the 'absenteeism_module' | |||
| 001 Are You Sure You're All Set_.html | 513 B | ||
| 002 Deploying the 'absenteeism_module' - Part I.mp4 | 8.38 MB | ||
| 002 Deploying the 'absenteeism_module' - Part I__en.srt | 4.86 KB | ||
| 003 Deploying the 'absenteeism_module' - Part II.mp4 | 25.99 MB | ||
| 003 Deploying the 'absenteeism_module' - Part II__en.srt | 429 B | ||
| 003 Deploying the 'absenteeism_module' - Part II_en.vtt | 6.76 KB | ||
| 004 Exporting the Obtained Data Set as a _.csv.html | 964 B | ||
| 29545348-Absenteeism-Exercise-Deploying-the-absenteeism-module.ipynb | 973 B | ||
| 29545372-Absenteeism-Exercise-Integration.ipynb | 62.35 KB | ||
| 29545374-absenteeism-module.py | 6.62 KB | ||
| 29545382-Absenteeism-new-data.csv | 1.87 KB | ||
| 29545384-model | 1.01 KB | ||
| 29545388-scaler | 1.86 KB | ||
| 61 - Case Study - Analyzing the Predicted Outputs in Tableau | |||
| 001 EXERCISE - Age vs Probability.html | 367 B | ||
| 002 Analyzing Age vs Probability in Tableau.mp4 | 38.69 MB | ||
| 002 Analyzing Age vs Probability in Tableau__en.srt | 10.22 KB | ||
| 003 EXERCISE - Reasons vs Probability.html | 385 B | ||
| 004 Analyzing Reasons vs Probability in Tableau.mp4 | 40.24 MB | ||
| 004 Analyzing Reasons vs Probability in Tableau__en.srt | 9.68 KB | ||
| 005 EXERCISE - Transportation Expense vs Probability.html | 529 B | ||
| 006 Analyzing Transportation Expense vs Probability in Tableau.mp4 | 10.87 MB | ||
| 006 Analyzing Transportation Expense vs Probability in Tableau__en.srt | 7.36 KB | ||
| 24453624-Absenteeism-predictions.csv | 2.1 KB | ||
| 29545266-Absenteeism-predictions.csv | 2.1 KB | ||
| 62 - Appendix - Additional Python Tools | |||
| 001 Using the .format() Method.mp4 | 21.67 MB | ||
| 001 Using the .format() Method__en.srt | 12.34 KB | ||
| 002 Iterating Over Range Objects.mp4 | 7.85 MB | ||
| 002 Iterating Over Range Objects__en.srt | 6.04 KB | ||
| 003 Introduction to Nested For Loops.mp4 | 12.26 MB | ||
| 003 Introduction to Nested For Loops__en.srt | 8.3 KB | ||
| 004 Triple Nested For Loops.mp4 | 19.4 MB | ||
| 004 Triple Nested For Loops__en.srt | 8 KB | ||
| 005 List Comprehensions.mp4 | 43.23 MB | ||
| 005 List Comprehensions__en.srt | 12.35 KB | ||
| 006 Anonymous (Lambda) Functions.mp4 | 33.71 MB | ||
| 006 Anonymous (Lambda) Functions__en.srt | 9.89 KB | ||
| 29535536-Additional-Python-Tools-Lectures.ipynb | 13.47 KB | ||
| 29535540-Additional-Python-Tools-Exercises.ipynb | 11.37 KB | ||
| 29535546-Additional-Python-Tools-Solutions.ipynb | 25.49 KB | ||
| 29535548-Additional-Python-Tools-Lectures.ipynb | 13.47 KB | ||
| 29535552-Additional-Python-Tools-Exercises.ipynb | 11.37 KB | ||
| 29535554-Additional-Python-Tools-Solutions.ipynb | 25.49 KB | ||
| 63 - Appendix - pandas Fundamentals | |||
| 001 Introduction to pandas Series.mp4 | 22.22 MB | ||
| 001 Introduction to pandas Series__en.srt | 10.67 KB | ||
| 002 Working with Methods in Python - Part I.mp4 | 16.8 MB | ||
| 002 Working with Methods in Python - Part I__en.srt | 6.92 KB | ||
| 003 Working with Methods in Python - Part II.mp4 | 5.77 MB | ||
| 003 Working with Methods in Python - Part II__en.srt | 3.6 KB | ||
| 004 Parameters and Arguments in pandas.mp4 | 15.45 MB | ||
| 004 Parameters and Arguments in pandas__en.srt | 5.5 KB | ||
| 005 Using .unique() and .nunique().mp4 | 26.33 MB | ||
| 005 Using .unique() and .nunique()__en.srt | 5.58 KB | ||
| 006 Using .sort_values().mp4 | 13.2 MB | ||
| 006 Using .sort_values()__en.srt | 5.54 KB | ||
| 007 Introduction to pandas DataFrames - Part I.mp4 | 10.6 MB | ||
| 007 Introduction to pandas DataFrames - Part I__en.srt | 7.08 KB | ||
| 008 Introduction to pandas DataFrames - Part II.mp4 | 17.83 MB | ||
| 008 Introduction to pandas DataFrames - Part II__en.srt | 7.61 KB | ||
| 009 pandas DataFrames - Common Attributes.mp4 | 29.8 MB | ||
| 009 pandas DataFrames - Common Attributes__en.srt | 6.25 KB | ||
| 010 Data Selection in pandas DataFrames.mp4 | 37.28 MB | ||
| 010 Data Selection in pandas DataFrames__en.srt | 10.04 KB | ||
| 011 pandas DataFrames - Indexing with .iloc[].mp4 | 23.54 MB | ||
| 011 pandas DataFrames - Indexing with .iloc[]__en.srt | 8.07 KB | ||
| 012 pandas DataFrames - Indexing with .loc[].mp4 | 20.72 MB | ||
| 012 pandas DataFrames - Indexing with .loc[]__en.srt | 5.51 KB | ||
| 64 - Bonus Lecture | |||
| 001 Bonus Lecture_ Next Steps.html | 2.84 KB | ||
| 35215106-365-Data-Science-Data-Science-Interview-Questions-Guide.pdf | 15.56 MB | ||
| Download Paid Udemy Courses For Free.url | 116 B | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| ▲ 1417 total files | |||
The Data Science Course 2022: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning
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