| 01 - Introduction to Course | |||
| 001 Welcome to the Course_.html | 1.64 KB | ||
| 002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP_.mp4 | 7.22 MB | ||
| 002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP___en.srt | 7.16 KB | ||
| 003 Anaconda Python and Jupyter Install and Setup.mp4 | 84.53 MB | ||
| 003 Anaconda Python and Jupyter Install and Setup__en.srt | 21.55 KB | ||
| 004 Note on Environment Setup - Please read me_.html | 857 B | ||
| 005 Environment Setup.mp4 | 35.71 MB | ||
| 005 Environment Setup__en.srt | 14.49 KB | ||
| 28813464-requirements.txt | 221 B | ||
| 33985574-UNZIP-FOR-NOTEBOOKS-FINAL.zip | 67.11 MB | ||
| 33985614-UNZIP-FOR-NOTEBOOKS-FINAL.zip | 67.11 MB | ||
| external-assets-links.txt | 132 B | ||
| 02 - OPTIONAL_ Python Crash Course | |||
| 001 OPTIONAL_ Python Crash Course.html | 472 B | ||
| 002 Python Crash Course - Part One.mp4 | 29.74 MB | ||
| 002 Python Crash Course - Part One__en.srt | 24.63 KB | ||
| 003 Python Crash Course - Part Two.mp4 | 57.63 MB | ||
| 003 Python Crash Course - Part Two__en.srt | 18.03 KB | ||
| 004 Python Crash Course - Part Three.mp4 | 32.01 MB | ||
| 004 Python Crash Course - Part Three__en.srt | 16.58 KB | ||
| 005 Python Crash Course - Exercise Questions.mp4 | 3.41 MB | ||
| 005 Python Crash Course - Exercise Questions__en.srt | 2.54 KB | ||
| 006 Python Crash Course - Exercise Solutions.mp4 | 48.7 MB | ||
| 006 Python Crash Course - Exercise Solutions__en.srt | 13.43 KB | ||
| 03 - Machine Learning Pathway Overview | |||
| 001 Machine Learning Pathway.mp4 | 14.1 MB | ||
| 001 Machine Learning Pathway__en.srt | 15.79 KB | ||
| 04 - NumPy | |||
| 001 Introduction to NumPy.mp4 | 3.37 MB | ||
| 001 Introduction to NumPy__en.srt | 3.01 KB | ||
| 002 NumPy Arrays.mp4 | 99.45 MB | ||
| 002 NumPy Arrays__en.srt | 31.91 KB | ||
| 003 NumPy Indexing and Selection.mp4 | 39.63 MB | ||
| 003 NumPy Indexing and Selection__en.srt | 16.22 KB | ||
| 004 NumPy Operations.mp4 | 36.06 MB | ||
| 004 NumPy Operations__en.srt | 12.05 KB | ||
| 005 NumPy Exercises.mp4 | 9.64 MB | ||
| 005 NumPy Exercises__en.srt | 2.07 KB | ||
| 006 Numpy Exercises - Solutions.mp4 | 34.88 MB | ||
| 006 Numpy Exercises - Solutions__en.srt | 10.87 KB | ||
| 05 - Pandas | |||
| 001 Introduction to Pandas.mp4 | 6.7 MB | ||
| 001 Introduction to Pandas__en.srt | 7.24 KB | ||
| 002 Series - Part One.mp4 | 28.62 MB | ||
| 002 Series - Part One__en.srt | 13.39 KB | ||
| 003 Series - Part Two.mp4 | 26.12 MB | ||
| 003 Series - Part Two__en.srt | 15.38 KB | ||
| 004 DataFrames - Part One - Creating a DataFrame.mp4 | 97.48 MB | ||
| 004 DataFrames - Part One - Creating a DataFrame__en.srt | 29 KB | ||
| 005 DataFrames - Part Two - Basic Properties.mp4 | 40.28 MB | ||
| 005 DataFrames - Part Two - Basic Properties__en.srt | 13.28 KB | ||
| 006 DataFrames - Part Three - Working with Columns.mp4 | 84.08 MB | ||
| 006 DataFrames - Part Three - Working with Columns__en.srt | 20.61 KB | ||
| 007 DataFrames - Part Four - Working with Rows.mp4 | 72.59 MB | ||
| 007 DataFrames - Part Four - Working with Rows__en.srt | 21.09 KB | ||
| 008 Pandas - Conditional Filtering.mp4 | 69.21 MB | ||
| 008 Pandas - Conditional Filtering__en.srt | 27.14 KB | ||
| 009 Pandas - Useful Methods - Apply on Single Column.mp4 | 53.72 MB | ||
| 009 Pandas - Useful Methods - Apply on Single Column__en.srt | 20.23 KB | ||
| 010 Pandas - Useful Methods - Apply on Multiple Columns.mp4 | 85.32 MB | ||
| 010 Pandas - Useful Methods - Apply on Multiple Columns__en.srt | 25.93 KB | ||
| 011 Pandas - Useful Methods - Statistical Information and Sorting.mp4 | 74.37 MB | ||
| 011 Pandas - Useful Methods - Statistical Information and Sorting__en.srt | 23.4 KB | ||
| 012 Missing Data - Overview.mp4 | 27.24 MB | ||
| 012 Missing Data - Overview__en.srt | 18.36 KB | ||
| 013 Missing Data - Pandas Operations.mp4 | 73.6 MB | ||
| 013 Missing Data - Pandas Operations__en.srt | 27.41 KB | ||
| 014 GroupBy Operations - Part One.mp4 | 86.96 MB | ||
| 014 GroupBy Operations - Part One__en.srt | 21.41 KB | ||
| 015 GroupBy Operations - Part Two - MultiIndex.mp4 | 92.86 MB | ||
| 015 GroupBy Operations - Part Two - MultiIndex__en.srt | 20.86 KB | ||
| 016 Combining DataFrames - Concatenation.mp4 | 36.84 MB | ||
| 016 Combining DataFrames - Concatenation__en.srt | 15.02 KB | ||
| 017 Combining DataFrames - Inner Merge.mp4 | 40.27 MB | ||
| 017 Combining DataFrames - Inner Merge__en.srt | 18.52 KB | ||
| 018 Combining DataFrames - Left and Right Merge.mp4 | 16.4 MB | ||
| 018 Combining DataFrames - Left and Right Merge__en.srt | 9.1 KB | ||
| 019 Combining DataFrames - Outer Merge.mp4 | 22.17 MB | ||
| 019 Combining DataFrames - Outer Merge__en.srt | 14.57 KB | ||
| 020 Pandas - Text Methods for String Data.mp4 | 45.12 MB | ||
| 020 Pandas - Text Methods for String Data__en.srt | 23.95 KB | ||
| 021 Pandas - Time Methods for Date and Time Data.mp4 | 80.19 MB | ||
| 021 Pandas - Time Methods for Date and Time Data__en.srt | 31.72 KB | ||
| 022 Pandas Input and Output - CSV Files.mp4 | 37.15 MB | ||
| 022 Pandas Input and Output - CSV Files__en.srt | 16.6 KB | ||
| 023 Pandas Input and Output - HTML Tables.mp4 | 102.34 MB | ||
| 023 Pandas Input and Output - HTML Tables__en.srt | 22.36 KB | ||
| 024 Pandas Input and Output - Excel Files.mp4 | 25.87 MB | ||
| 024 Pandas Input and Output - Excel Files__en.srt | 10.88 KB | ||
| 025 Pandas Input and Output - SQL Databases.mp4 | 95.98 MB | ||
| 025 Pandas Input and Output - SQL Databases__en.srt | 29.43 KB | ||
| 026 Pandas Pivot Tables.mp4 | 129.09 MB | ||
| 026 Pandas Pivot Tables__en.srt | 32.18 KB | ||
| 027 Pandas Project Exercise Overview.mp4 | 39.43 MB | ||
| 027 Pandas Project Exercise Overview__en.srt | 9.59 KB | ||
| 028 Pandas Project Exercise Solutions.mp4 | 172.55 MB | ||
| 028 Pandas Project Exercise Solutions__en.srt | 38.77 KB | ||
| 06 - Matplotlib | |||
| 001 Introduction to Matplotlib.mp4 | 6.55 MB | ||
| 001 Introduction to Matplotlib__en.srt | 6.72 KB | ||
| 002 Matplotlib Basics.mp4 | 31.07 MB | ||
| 002 Matplotlib Basics__en.srt | 19.64 KB | ||
| 003 Matplotlib - Understanding the Figure Object.mp4 | 11.7 MB | ||
| 003 Matplotlib - Understanding the Figure Object__en.srt | 11.55 KB | ||
| 004 Matplotlib - Implementing Figures and Axes.mp4 | 34.86 MB | ||
| 004 Matplotlib - Implementing Figures and Axes__en.srt | 20.97 KB | ||
| 005 Matplotlib - Figure Parameters.mp4 | 13.06 MB | ||
| 005 Matplotlib - Figure Parameters__en.srt | 7.65 KB | ||
| 006 Matplotlib - Subplots Functionality.mp4 | 96.57 MB | ||
| 006 Matplotlib - Subplots Functionality__en.srt | 28.63 KB | ||
| 007 Matplotlib Styling - Legends.mp4 | 16.19 MB | ||
| 007 Matplotlib Styling - Legends__en.srt | 10.36 KB | ||
| 008 Matplotlib Styling - Colors and Styles.mp4 | 44.27 MB | ||
| 008 Matplotlib Styling - Colors and Styles__en.srt | 21.04 KB | ||
| 009 Advanced Matplotlib Commands (Optional).mp4 | 25.19 MB | ||
| 009 Advanced Matplotlib Commands (Optional)__en.srt | 6.49 KB | ||
| 010 Matplotlib Exercise Questions Overview.mp4 | 48.99 MB | ||
| 010 Matplotlib Exercise Questions Overview__en.srt | 9.33 KB | ||
| 011 Matplotlib Exercise Questions - Solutions.mp4 | 105.86 MB | ||
| 011 Matplotlib Exercise Questions - Solutions__en.srt | 24.53 KB | ||
| 07 - Seaborn Data Visualizations | |||
| 001 Introduction to Seaborn.mp4 | 5.74 MB | ||
| 001 Introduction to Seaborn__en.srt | 6.51 KB | ||
| 002 Scatterplots with Seaborn.mp4 | 111.3 MB | ||
| 002 Scatterplots with Seaborn__en.srt | 29.72 KB | ||
| 003 Distribution Plots - Part One - Understanding Plot Types.mp4 | 15.03 MB | ||
| 003 Distribution Plots - Part One - Understanding Plot Types__en.srt | 15 KB | ||
| 004 Distribution Plots - Part Two - Coding with Seaborn.mp4 | 59.21 MB | ||
| 004 Distribution Plots - Part Two - Coding with Seaborn__en.srt | 24.79 KB | ||
| 005 Categorical Plots - Statistics within Categories - Understanding Plot Types.mp4 | 15.98 MB | ||
| 005 Categorical Plots - Statistics within Categories - Understanding Plot Types__en.srt | 8.8 KB | ||
| 006 Categorical Plots - Statistics within Categories - Coding with Seaborn.mp4 | 51.65 MB | ||
| 006 Categorical Plots - Statistics within Categories - Coding with Seaborn__en.srt | 14.61 KB | ||
| 007 Categorical Plots - Distributions within Categories - Understanding Plot Types.mp4 | 44.96 MB | ||
| 007 Categorical Plots - Distributions within Categories - Understanding Plot Types__en.srt | 20.1 KB | ||
| 008 Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4 | 84.57 MB | ||
| 008 Categorical Plots - Distributions within Categories - Coding with Seaborn__en.srt | 28.26 KB | ||
| 009 Seaborn - Comparison Plots - Understanding the Plot Types.mp4 | 10.57 MB | ||
| 009 Seaborn - Comparison Plots - Understanding the Plot Types__en.srt | 8.74 KB | ||
| 010 Seaborn - Comparison Plots - Coding with Seaborn.mp4 | 51.16 MB | ||
| 010 Seaborn - Comparison Plots - Coding with Seaborn__en.srt | 15.71 KB | ||
| 011 Seaborn Grid Plots.mp4 | 87.01 MB | ||
| 011 Seaborn Grid Plots__en.srt | 20.5 KB | ||
| 012 Seaborn - Matrix Plots.mp4 | 61.47 MB | ||
| 012 Seaborn - Matrix Plots__en.srt | 21.09 KB | ||
| 013 Seaborn Plot Exercises Overview.mp4 | 47.88 MB | ||
| 013 Seaborn Plot Exercises Overview__en.srt | 11.26 KB | ||
| 014 Seaborn Plot Exercises Solutions.mp4 | 105.72 MB | ||
| 014 Seaborn Plot Exercises Solutions__en.srt | 22.39 KB | ||
| 08 - Data Analysis and Visualization Capstone Project Exercise | |||
| 001 Capstone Project Overview.mp4 | 31.11 MB | ||
| 001 Capstone Project Overview__en.srt | 20.6 KB | ||
| 002 Capstone Project Solutions - Part One.mp4 | 110.61 MB | ||
| 002 Capstone Project Solutions - Part One__en.srt | 26.84 KB | ||
| 003 Capstone Project Solutions - Part Two.mp4 | 106.18 MB | ||
| 003 Capstone Project Solutions - Part Two__en.srt | 23.48 KB | ||
| 004 Capstone Project Solutions - Part Three.mp4 | 137.39 MB | ||
| 004 Capstone Project Solutions - Part Three__en.srt | 30.88 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 09 - Machine Learning Concepts Overview | |||
| 001 Introduction to Machine Learning Overview Section.mp4 | 13.17 MB | ||
| 001 Introduction to Machine Learning Overview Section__en.srt | 8.58 KB | ||
| 002 Why Machine Learning_.mp4 | 21.04 MB | ||
| 002 Why Machine Learning___en.srt | 14.66 KB | ||
| 003 Types of Machine Learning Algorithms.mp4 | 18.08 MB | ||
| 003 Types of Machine Learning Algorithms__en.srt | 11.63 KB | ||
| 004 Supervised Machine Learning Process.mp4 | 33.53 MB | ||
| 004 Supervised Machine Learning Process__en.srt | 19.77 KB | ||
| 005 Companion Book - Introduction to Statistical Learning.mp4 | 5.11 MB | ||
| 005 Companion Book - Introduction to Statistical Learning__en.srt | 4.66 KB | ||
| 10 - Linear Regression | |||
| 001 Introduction to Linear Regression Section.mp4 | 2.58 MB | ||
| 001 Introduction to Linear Regression Section__en.srt | 2.68 KB | ||
| 002 Linear Regression - Algorithm History.mp4 | 54.82 MB | ||
| 002 Linear Regression - Algorithm History__en.srt | 13.09 KB | ||
| 003 Linear Regression - Understanding Ordinary Least Squares.mp4 | 86.37 MB | ||
| 003 Linear Regression - Understanding Ordinary Least Squares__en.srt | 22.53 KB | ||
| 004 Linear Regression - Cost Functions.mp4 | 16.63 MB | ||
| 004 Linear Regression - Cost Functions__en.srt | 11.46 KB | ||
| 005 Linear Regression - Gradient Descent.mp4 | 29.21 MB | ||
| 005 Linear Regression - Gradient Descent__en.srt | 16.73 KB | ||
| 006 Python coding Simple Linear Regression.mp4 | 70.14 MB | ||
| 006 Python coding Simple Linear Regression__en.srt | 28.14 KB | ||
| 007 Overview of Scikit-Learn and Python.mp4 | 31.44 MB | ||
| 007 Overview of Scikit-Learn and Python__en.srt | 10.14 KB | ||
| 007 Overview of Scikit-Learn and Python_en.vtt | 10.96 KB | ||
| 008 Linear Regression - Scikit-Learn Train Test Split.mp4 | 61.42 MB | ||
| 008 Linear Regression - Scikit-Learn Train Test Split__en.srt | 23.78 KB | ||
| 009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp4 | 53.4 MB | ||
| 009 Linear Regression - Scikit-Learn Performance Evaluation - Regression__en.srt | 23 KB | ||
| 010 Linear Regression - Residual Plots.mp4 | 44.02 MB | ||
| 010 Linear Regression - Residual Plots__en.srt | 20.22 KB | ||
| 011 Linear Regression - Model Deployment and Coefficient Interpretation.mp4 | 81.14 MB | ||
| 011 Linear Regression - Model Deployment and Coefficient Interpretation__en.srt | 25.62 KB | ||
| 012 Polynomial Regression - Theory and Motivation.mp4 | 22.25 MB | ||
| 012 Polynomial Regression - Theory and Motivation__en.srt | 11.21 KB | ||
| 013 Polynomial Regression - Creating Polynomial Features.mp4 | 40.09 MB | ||
| 013 Polynomial Regression - Creating Polynomial Features__en.srt | 16.39 KB | ||
| 014 Polynomial Regression - Training and Evaluation.mp4 | 36.3 MB | ||
| 014 Polynomial Regression - Training and Evaluation__en.srt | 14.17 KB | ||
| 015 Bias Variance Trade-Off.mp4 | 36.18 MB | ||
| 015 Bias Variance Trade-Off__en.srt | 15.94 KB | ||
| 016 Polynomial Regression - Choosing Degree of Polynomial.mp4 | 55.68 MB | ||
| 016 Polynomial Regression - Choosing Degree of Polynomial__en.srt | 19.88 KB | ||
| 017 Polynomial Regression - Model Deployment.mp4 | 23.22 MB | ||
| 017 Polynomial Regression - Model Deployment__en.srt | 8.38 KB | ||
| 018 Regularization Overview.mp4 | 15.52 MB | ||
| 018 Regularization Overview__en.srt | 10.33 KB | ||
| 019 Feature Scaling.mp4 | 24.34 MB | ||
| 019 Feature Scaling__en.srt | 14.83 KB | ||
| 020 Introduction to Cross Validation.mp4 | 32.97 MB | ||
| 020 Introduction to Cross Validation__en.srt | 19.81 KB | ||
| 021 Regularization Data Setup.mp4 | 20.16 MB | ||
| 021 Regularization Data Setup__en.srt | 12.42 KB | ||
| 022 L2 Regularization - Ridge Regression Theory.mp4 | 61.3 MB | ||
| 022 L2 Regularization - Ridge Regression Theory__en.srt | 20.72 KB | ||
| 023 L2 Regularization - Ridge Regression - Python Implementation.mp4 | 89.37 MB | ||
| 023 L2 Regularization - Ridge Regression - Python Implementation__en.srt | 10.89 KB | ||
| 023 L2 Regularization - Ridge Regression - Python Implementation_en.vtt | 22.98 KB | ||
| 024 L1 Regularization - Lasso Regression - Background and Implementation.mp4 | 94.65 MB | ||
| 024 L1 Regularization - Lasso Regression - Background and Implementation__en.srt | 5.4 KB | ||
| 024 L1 Regularization - Lasso Regression - Background and Implementation_en.vtt | 19.64 KB | ||
| 025 L1 and L2 Regularization - Elastic Net.mp4 | 66.4 MB | ||
| 025 L1 and L2 Regularization - Elastic Net__en.srt | 16.97 KB | ||
| 025 L1 and L2 Regularization - Elastic Net_en.vtt | 22.62 KB | ||
| 026 Linear Regression Project - Data Overview.mp4 | 16.94 MB | ||
| 026 Linear Regression Project - Data Overview__en.srt | 7.67 KB | ||
| 11 - Feature Engineering and Data Preparation | |||
| 001 A note from Jose on Feature Engineering and Data Preparation.html | 990 B | ||
| 002 Introduction to Feature Engineering and Data Preparation.mp4 | 36.11 MB | ||
| 002 Introduction to Feature Engineering and Data Preparation__en.srt | 24.1 KB | ||
| 003 Dealing with Outliers.mp4 | 103.32 MB | ||
| 003 Dealing with Outliers__en.srt | 41.2 KB | ||
| 004 Dealing with Missing Data _ Part One - Evaluation of Missing Data.mp4 | 19.05 MB | ||
| 004 Dealing with Missing Data _ Part One - Evaluation of Missing Data__en.srt | 16.97 KB | ||
| 005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows.mp4 | 117.56 MB | ||
| 005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows__en.srt | 31.42 KB | ||
| 006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns.mp4 | 105.22 MB | ||
| 006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns__en.srt | 36.75 KB | ||
| 007 Dealing with Categorical Data - Encoding Options.mp4 | 58.87 MB | ||
| 007 Dealing with Categorical Data - Encoding Options__en.srt | 20.1 KB | ||
| 12 - Cross Validation , Grid Search, and the Linear Regression Project | |||
| 001 Section Overview and Introduction.mp4 | 5.61 MB | ||
| 001 Section Overview and Introduction__en.srt | 5.05 KB | ||
| 002 Cross Validation - Test _ Train Split.mp4 | 46.86 MB | ||
| 002 Cross Validation - Test _ Train Split__en.srt | 17.43 KB | ||
| 003 Cross Validation - Test _ Validation _ Train Split.mp4 | 59.41 MB | ||
| 003 Cross Validation - Test _ Validation _ Train Split__en.srt | 21.65 KB | ||
| 004 Cross Validation - cross_val_score.mp4 | 44.46 MB | ||
| 004 Cross Validation - cross_val_score__en.srt | 8.14 KB | ||
| 004 Cross Validation - cross_val_score_en.vtt | 15.2 KB | ||
| 005 Cross Validation - cross_validate.mp4 | 45.01 MB | ||
| 005 Cross Validation - cross_validate__en.srt | 11.23 KB | ||
| 006 Grid Search.mp4 | 73.19 MB | ||
| 006 Grid Search__en.srt | 19.26 KB | ||
| 007 Linear Regression Project Overview.mp4 | 23.63 MB | ||
| 007 Linear Regression Project Overview__en.srt | 5.82 KB | ||
| 008 Linear Regression Project - Solutions.mp4 | 91.23 MB | ||
| 008 Linear Regression Project - Solutions__en.srt | 8.8 KB | ||
| 008 Linear Regression Project - Solutions_en.vtt | 15.87 KB | ||
| 13 - Logistic Regression | |||
| 001 Early Bird Note on Downloading .zip for Logistic Regression Notes.html | 523 B | ||
| 002 Introduction to Logistic Regression Section.mp4 | 13.93 MB | ||
| 002 Introduction to Logistic Regression Section__en.srt | 8.39 KB | ||
| 003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function.mp4 | 17.31 MB | ||
| 003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function__en.srt | 8.09 KB | ||
| 004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic.mp4 | 8.03 MB | ||
| 004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic__en.srt | 7.27 KB | ||
| 005 Logistic Regression - Theory and Intuition - Linear to Logistic Math.mp4 | 36.04 MB | ||
| 005 Logistic Regression - Theory and Intuition - Linear to Logistic Math__en.srt | 24.81 KB | ||
| 006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood.mp4 | 54.91 MB | ||
| 006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood__en.srt | 22.96 KB | ||
| 007 Logistic Regression with Scikit-Learn - Part One - EDA.mp4 | 62.45 MB | ||
| 007 Logistic Regression with Scikit-Learn - Part One - EDA__en.srt | 21.9 KB | ||
| 008 Logistic Regression with Scikit-Learn - Part Two - Model Training.mp4 | 32.57 MB | ||
| 008 Logistic Regression with Scikit-Learn - Part Two - Model Training__en.srt | 9.57 KB | ||
| 009 Classification Metrics - Confusion Matrix and Accuracy.mp4 | 21.72 MB | ||
| 009 Classification Metrics - Confusion Matrix and Accuracy__en.srt | 13.93 KB | ||
| 010 Classification Metrics - Precison, Recall, F1-Score.mp4 | 33.14 MB | ||
| 010 Classification Metrics - Precison, Recall, F1-Score__en.srt | 8.34 KB | ||
| 011 Classification Metrics - ROC Curves.mp4 | 16.07 MB | ||
| 011 Classification Metrics - ROC Curves__en.srt | 11.07 KB | ||
| 012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation.mp4 | 57.03 MB | ||
| 012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation__en.srt | 23.43 KB | ||
| 013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA.mp4 | 37.38 MB | ||
| 013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA__en.srt | 12.01 KB | ||
| 014 Multi-Class Classification with Logistic Regression - Part Two - Model.mp4 | 105.09 MB | ||
| 014 Multi-Class Classification with Logistic Regression - Part Two - Model__en.srt | 23.82 KB | ||
| 015 Logistic Regression Exercise Project Overview.mp4 | 24.29 MB | ||
| 015 Logistic Regression Exercise Project Overview__en.srt | 6.49 KB | ||
| 016 Logistic Regression Project Exercise - Solutions.mp4 | 161.29 MB | ||
| 016 Logistic Regression Project Exercise - Solutions__en.srt | 14.33 KB | ||
| 016 Logistic Regression Project Exercise - Solutions_en.vtt | 30.89 KB | ||
| 29304858-11-Logistic-Regression-Models.zip | 2.02 MB | ||
| 14 - KNN - K Nearest Neighbors | |||
| 001 Introduction to KNN Section.mp4 | 3.65 MB | ||
| 001 Introduction to KNN Section__en.srt | 3.63 KB | ||
| 002 KNN Classification - Theory and Intuition.mp4 | 23.55 MB | ||
| 002 KNN Classification - Theory and Intuition__en.srt | 16.93 KB | ||
| 003 KNN Coding with Python - Part One.mp4 | 61.55 MB | ||
| 003 KNN Coding with Python - Part One__en.srt | 10.99 KB | ||
| 003 KNN Coding with Python - Part One_en.vtt | 19.38 KB | ||
| 004 KNN Coding with Python - Part Two - Choosing K.mp4 | 102.86 MB | ||
| 004 KNN Coding with Python - Part Two - Choosing K__en.srt | 3.94 KB | ||
| 004 KNN Coding with Python - Part Two - Choosing K_en.vtt | 30.67 KB | ||
| 005 KNN Classification Project Exercise Overview.mp4 | 21.12 MB | ||
| 005 KNN Classification Project Exercise Overview__en.srt | 5.23 KB | ||
| 006 KNN Classification Project Exercise Solutions.mp4 | 105.03 MB | ||
| 006 KNN Classification Project Exercise Solutions__en.srt | 8.62 KB | ||
| 006 KNN Classification Project Exercise Solutions_en.vtt | 18.55 KB | ||
| 29434428-12-K-Nearest-Neighbors.zip | 1.35 MB | ||
| 15 - Support Vector Machines | |||
| 001 Introduction to Support Vector Machines.mp4 | 2.79 MB | ||
| 001 Introduction to Support Vector Machines__en.srt | 2.3 KB | ||
| 002 History of Support Vector Machines.mp4 | 15.54 MB | ||
| 002 History of Support Vector Machines__en.srt | 6.53 KB | ||
| 003 SVM - Theory and Intuition - Hyperplanes and Margins.mp4 | 47.74 MB | ||
| 003 SVM - Theory and Intuition - Hyperplanes and Margins__en.srt | 18.58 KB | ||
| 004 SVM - Theory and Intuition - Kernel Intuition.mp4 | 9.83 MB | ||
| 004 SVM - Theory and Intuition - Kernel Intuition__en.srt | 7.11 KB | ||
| 005 SVM - Theory and Intuition - Kernel Trick and Mathematics.mp4 | 52.62 MB | ||
| 005 SVM - Theory and Intuition - Kernel Trick and Mathematics__en.srt | 29.3 KB | ||
| 006 SVM with Scikit-Learn and Python - Classification Part One.mp4 | 46.28 MB | ||
| 006 SVM with Scikit-Learn and Python - Classification Part One__en.srt | 16.39 KB | ||
| 007 SVM with Scikit-Learn and Python - Classification Part Two.mp4 | 90.63 MB | ||
| 007 SVM with Scikit-Learn and Python - Classification Part Two__en.srt | 20.73 KB | ||
| 007 SVM with Scikit-Learn and Python - Classification Part Two_en.vtt | 20.98 KB | ||
| 008 SVM with Scikit-Learn and Python - Regression Tasks.mp4 | 76.27 MB | ||
| 008 SVM with Scikit-Learn and Python - Regression Tasks__en.srt | 25.67 KB | ||
| 008 SVM with Scikit-Learn and Python - Regression Tasks_en.vtt | 26.15 KB | ||
| 009 Support Vector Machine Project Overview.mp4 | 34.84 MB | ||
| 009 Support Vector Machine Project Overview__en.srt | 6.87 KB | ||
| 010 Support Vector Machine Project Solutions.mp4 | 93.36 MB | ||
| 010 Support Vector Machine Project Solutions__en.srt | 12.75 KB | ||
| 010 Support Vector Machine Project Solutions_en.vtt | 22.5 KB | ||
| 29902052-13-Support-Vector-Machines.zip | 1.51 MB | ||
| 16 - Tree Based Methods_ Decision Tree Learning | |||
| 001 Introduction to Tree Based Methods.mp4 | 2.33 MB | ||
| 001 Introduction to Tree Based Methods__en.srt | 2.21 KB | ||
| 002 Decision Tree - History.mp4 | 35.58 MB | ||
| 002 Decision Tree - History__en.srt | 13.15 KB | ||
| 003 Decision Tree - Terminology.mp4 | 7.29 MB | ||
| 003 Decision Tree - Terminology__en.srt | 6.43 KB | ||
| 004 Decision Tree - Understanding Gini Impurity.mp4 | 19.45 MB | ||
| 004 Decision Tree - Understanding Gini Impurity__en.srt | 11.11 KB | ||
| 005 Constructing Decision Trees with Gini Impurity - Part One.mp4 | 17.69 MB | ||
| 005 Constructing Decision Trees with Gini Impurity - Part One__en.srt | 11.48 KB | ||
| 006 Constructing Decision Trees with Gini Impurity - Part Two.mp4 | 52.35 MB | ||
| 006 Constructing Decision Trees with Gini Impurity - Part Two__en.srt | 16.42 KB | ||
| 007 Coding Decision Trees - Part One - The Data.mp4 | 98.72 MB | ||
| 007 Coding Decision Trees - Part One - The Data__en.srt | 29.28 KB | ||
| 008 Coding Decision Trees - Part Two -Creating the Model.mp4 | 115.8 MB | ||
| 008 Coding Decision Trees - Part Two -Creating the Model__en.srt | 32.7 KB | ||
| 30205020-14-Decision-Trees.zip | 1.79 MB | ||
| 17 - Random Forests | |||
| 001 Introduction to Random Forests Section.mp4 | 2.87 MB | ||
| 001 Introduction to Random Forests Section__en.srt | 2.81 KB | ||
| 002 Random Forests - History and Motivation.mp4 | 24 MB | ||
| 002 Random Forests - History and Motivation__en.srt | 17.22 KB | ||
| 003 Random Forests - Key Hyperparameters.mp4 | 8.27 MB | ||
| 003 Random Forests - Key Hyperparameters__en.srt | 4.45 KB | ||
| 004 Random Forests - Number of Estimators and Features in Subsets.mp4 | 27.31 MB | ||
| 004 Random Forests - Number of Estimators and Features in Subsets__en.srt | 16.17 KB | ||
| 005 Random Forests - Bootstrapping and Out-of-Bag Error.mp4 | 32.72 MB | ||
| 005 Random Forests - Bootstrapping and Out-of-Bag Error__en.srt | 17.97 KB | ||
| 006 Coding Classification with Random Forest Classifier - Part One.mp4 | 52.1 MB | ||
| 006 Coding Classification with Random Forest Classifier - Part One__en.srt | 9.92 KB | ||
| 006 Coding Classification with Random Forest Classifier - Part One_en.vtt | 15.78 KB | ||
| 007 Coding Classification with Random Forest Classifier - Part Two.mp4 | 130.37 MB | ||
| 007 Coding Classification with Random Forest Classifier - Part Two__en.srt | 20.04 KB | ||
| 007 Coding Classification with Random Forest Classifier - Part Two_en.vtt | 27.9 KB | ||
| 008 Coding Regression with Random Forest Regressor - Part One - Data.mp4 | 13.68 MB | ||
| 008 Coding Regression with Random Forest Regressor - Part One - Data__en.srt | 6.86 KB | ||
| 009 Coding Regression with Random Forest Regressor - Part Two - Basic Models.mp4 | 85.01 MB | ||
| 009 Coding Regression with Random Forest Regressor - Part Two - Basic Models__en.srt | 20.42 KB | ||
| 010 Coding Regression with Random Forest Regressor - Part Three - Polynomials.mp4 | 45.54 MB | ||
| 010 Coding Regression with Random Forest Regressor - Part Three - Polynomials__en.srt | 15.34 KB | ||
| 011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models.mp4 | 50.67 MB | ||
| 011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models__en.srt | 15.45 KB | ||
| 30930956-15-Random-Forests.zip | 3.93 MB | ||
| 30930966-data-banknote-authentication.csv | 45.38 KB | ||
| 18 - Boosting Methods | |||
| 001 Introduction to Boosting Section.mp4 | 2.99 MB | ||
| 001 Introduction to Boosting Section__en.srt | 2.67 KB | ||
| 002 Boosting Methods - Motivation and History.mp4 | 21.98 MB | ||
| 002 Boosting Methods - Motivation and History__en.srt | 8.96 KB | ||
| 003 AdaBoost Theory and Intuition.mp4 | 41.53 MB | ||
| 003 AdaBoost Theory and Intuition__en.srt | 28.95 KB | ||
| 004 AdaBoost Coding Part One - The Data.mp4 | 42.25 MB | ||
| 004 AdaBoost Coding Part One - The Data__en.srt | 16.66 KB | ||
| 005 AdaBoost Coding Part Two - The Model.mp4 | 63.11 MB | ||
| 005 AdaBoost Coding Part Two - The Model__en.srt | 26.61 KB | ||
| 006 Gradient Boosting Theory.mp4 | 22.96 MB | ||
| 006 Gradient Boosting Theory__en.srt | 16.11 KB | ||
| 007 Gradient Boosting Coding Walkthrough.mp4 | 57.91 MB | ||
| 007 Gradient Boosting Coding Walkthrough__en.srt | 8.9 KB | ||
| 007 Gradient Boosting Coding Walkthrough_en.vtt | 17.5 KB | ||
| 31286608-16-Boosted-Trees.zip | 917.98 KB | ||
| 31286610-mushrooms.csv | 365.24 KB | ||
| 19 - Supervised Learning Capstone Project | |||
| 001 Introduction to Supervised Learning Capstone Project.mp4 | 29.84 MB | ||
| 001 Introduction to Supervised Learning Capstone Project__en.srt | 25.69 KB | ||
| 002 Solution Walkthrough - Supervised Learning Project - Data and EDA.mp4 | 106.1 MB | ||
| 002 Solution Walkthrough - Supervised Learning Project - Data and EDA__en.srt | 29.67 KB | ||
| 003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis.mp4 | 130.14 MB | ||
| 003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis__en.srt | 38.72 KB | ||
| 004 Solution Walkthrough - Supervised Learning Project - Tree Models.mp4 | 114.21 MB | ||
| 004 Solution Walkthrough - Supervised Learning Project - Tree Models__en.srt | 4.2 KB | ||
| 004 Solution Walkthrough - Supervised Learning Project - Tree Models_en.vtt | 29.4 KB | ||
| 31389398-17-Supervised-Learning-Capstone-Project.zip | 7.04 MB | ||
| 31389400-Telco-Customer-Churn.csv | 953.66 KB | ||
| 20 - Naive Bayes Classification and Natural Language Processing | |||
| 001 Introduction to NLP and Naive Bayes Section.mp4 | 4.22 MB | ||
| 001 Introduction to NLP and Naive Bayes Section__en.srt | 3.69 KB | ||
| 002 Naive Bayes Algorithm - Part One - Bayes Theorem.mp4 | 22.04 MB | ||
| 002 Naive Bayes Algorithm - Part One - Bayes Theorem__en.srt | 11.85 KB | ||
| 003 Naive Bayes Algorithm - Part Two - Model Algorithm.mp4 | 48.61 MB | ||
| 003 Naive Bayes Algorithm - Part Two - Model Algorithm__en.srt | 26.35 KB | ||
| 004 Feature Extraction from Text - Part One - Theory and Intuition.mp4 | 29.4 MB | ||
| 006 Feature Extraction from Text - Coding with Scikit-Learn.mp4 | 50.39 MB | ||
| 006 Feature Extraction from Text - Coding with Scikit-Learn__en.srt | 16.67 KB | ||
| 007 Natural Language Processing - Classification of Text - Part One.mp4 | 28.26 MB | ||
| 008 Natural Language Processing - Classification of Text - Part Two.mp4 | 34.77 MB | ||
| 009 Text Classification Project Exercise Overview.mp4 | 30.54 MB | ||
| 009 Text Classification Project Exercise Overview__en.srt | 7.86 KB | ||
| 010 Text Classification Project Exercise Solutions.mp4 | 100.59 MB | ||
| 010 Text Classification Project Exercise Solutions__en.srt | 19.4 KB | ||
| 010 Text Classification Project Exercise Solutions_en.vtt | 21.33 KB | ||
| 31640094-18-Naive-Bayes-and-NLP.zip | 192.48 KB | ||
| 31640102-airline-tweets.csv | 3.26 MB | ||
| 31640132-moviereviews.csv | 7.22 MB | ||
| 21 - Unsupervised Learning | |||
| 001 Unsupervised Learning Overview.mp4 | 13.75 MB | ||
| 001 Unsupervised Learning Overview__en.srt | 12.86 KB | ||
| 22 - K-Means Clustering | |||
| 001 Introduction to K-Means Clustering Section.mp4 | 3.55 MB | ||
| 001 Introduction to K-Means Clustering Section__en.srt | 3.5 KB | ||
| 002 Clustering General Overview.mp4 | 24.86 MB | ||
| 002 Clustering General Overview__en.srt | 16.5 KB | ||
| 003 K-Means Clustering Theory.mp4 | 52.49 MB | ||
| 003 K-Means Clustering Theory__en.srt | 17.25 KB | ||
| 004 K-Means Clustering - Coding Part One.mp4 | 97.9 MB | ||
| 004 K-Means Clustering - Coding Part One__en.srt | 30.36 KB | ||
| 005 K-Means Clustering Coding Part Two.mp4 | 80.85 MB | ||
| 005 K-Means Clustering Coding Part Two__en.srt | 26.55 KB | ||
| 006 K-Means Clustering Coding Part Three.mp4 | 59.77 MB | ||
| 006 K-Means Clustering Coding Part Three__en.srt | 21.38 KB | ||
| 007 K-Means Color Quantization - Part One.mp4 | 80.57 MB | ||
| 007 K-Means Color Quantization - Part One__en.srt | 20.38 KB | ||
| 008 K-Means Color Quantization - Part Two.mp4 | 65.03 MB | ||
| 008 K-Means Color Quantization - Part Two__en.srt | 21.27 KB | ||
| 009 K-Means Clustering Exercise Overview.mp4 | 59.48 MB | ||
| 009 K-Means Clustering Exercise Overview__en.srt | 13.43 KB | ||
| 010 K-Means Clustering Exercise Solution - Part One.mp4 | 79.92 MB | ||
| 010 K-Means Clustering Exercise Solution - Part One__en.srt | 21.1 KB | ||
| 011 K-Means Clustering Exercise Solution - Part Two.mp4 | 108.19 MB | ||
| 011 K-Means Clustering Exercise Solution - Part Two__en.srt | 23.53 KB | ||
| 012 K-Means Clustering Exercise Solution - Part Three.mp4 | 62.5 MB | ||
| 012 K-Means Clustering Exercise Solution - Part Three__en.srt | 12.15 KB | ||
| 32407448-20-Kmeans-Clustering.zip | 5.83 MB | ||
| 32407452-bank-full.csv | 4.95 MB | ||
| 32407456-CIA-Country-Facts.csv | 32.7 KB | ||
| 32407460-country-iso-codes.csv | 7.94 KB | ||
| 33555798-palm-trees.jpg?042148 | 172.74 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 23 - Hierarchical Clustering | |||
| 001 Introduction to Hierarchical Clustering.mp4 | 1.67 MB | ||
| 001 Introduction to Hierarchical Clustering__en.srt | 1.17 KB | ||
| 002 Hierarchical Clustering - Theory and Intuition.mp4 | 52.07 MB | ||
| 002 Hierarchical Clustering - Theory and Intuition__en.srt | 17.29 KB | ||
| 003 Hierarchical Clustering - Coding Part One - Data and Visualization.mp4 | 114.98 MB | ||
| 003 Hierarchical Clustering - Coding Part One - Data and Visualization__en.srt | 25.38 KB | ||
| 004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4 | 209.23 MB | ||
| 004 Hierarchical Clustering - Coding Part Two - Scikit-Learn__en.srt | 42.26 KB | ||
| 33028500-21-Hierarchical-Clustering.zip | 621.63 KB | ||
| 33028506-cluster-mpg.csv | 20.83 KB | ||
| 24 - DBSCAN - Density-based spatial clustering of applications with noise | |||
| 001 Introduction to DBSCAN Section.mp4 | 1.8 MB | ||
| 001 Introduction to DBSCAN Section__en.srt | 1.34 KB | ||
| 002 DBSCAN - Theory and Intuition.mp4 | 109.09 MB | ||
| 002 DBSCAN - Theory and Intuition__en.srt | 26.51 KB | ||
| 003 DBSCAN versus K-Means Clustering.mp4 | 66.64 MB | ||
| 003 DBSCAN versus K-Means Clustering__en.srt | 17.37 KB | ||
| 004 DBSCAN - Hyperparameter Theory.mp4 | 13.86 MB | ||
| 004 DBSCAN - Hyperparameter Theory__en.srt | 10.7 KB | ||
| 005 DBSCAN - Hyperparameter Tuning Methods.mp4 | 105.08 MB | ||
| 005 DBSCAN - Hyperparameter Tuning Methods__en.srt | 32.66 KB | ||
| 006 DBSCAN - Outlier Project Exercise Overview.mp4 | 50.27 MB | ||
| 006 DBSCAN - Outlier Project Exercise Overview__en.srt | 9.96 KB | ||
| 007 DBSCAN - Outlier Project Exercise Solutions.mp4 | 127.93 MB | ||
| 007 DBSCAN - Outlier Project Exercise Solutions__en.srt | 38.12 KB | ||
| 33643014-22-DBSCAN.zip | 3.51 MB | ||
| 33643060-cluster-circles.csv | 59.88 KB | ||
| 33643066-wholesome-customers-data.csv | 14.67 KB | ||
| 33643070-cluster-two-blobs-outliers.csv | 38.29 KB | ||
| 33643072-cluster-two-blobs.csv | 38.26 KB | ||
| 33643080-cluster-blobs.csv | 55.86 KB | ||
| 33643082-cluster-moons.csv | 58.7 KB | ||
| external-assets-links.txt | 103 B | ||
| 25 - PCA - Principal Component Analysis and Manifold Learning | |||
| 001 Introduction to Principal Component Analysis.mp4 | 5.08 MB | ||
| 001 Introduction to Principal Component Analysis__en.srt | 3.97 KB | ||
| 002 PCA Theory and Intuition - Part One.mp4 | 29.72 MB | ||
| 002 PCA Theory and Intuition - Part One__en.srt | 15.6 KB | ||
| 003 PCA Theory and Intuition - Part Two.mp4 | 19.04 MB | ||
| 003 PCA Theory and Intuition - Part Two__en.srt | 16.36 KB | ||
| 004 PCA - Manual Implementation in Python.mp4 | 95.04 MB | ||
| 004 PCA - Manual Implementation in Python__en.srt | 26.27 KB | ||
| 005 PCA - SciKit-Learn.mp4 | 74.09 MB | ||
| 005 PCA - SciKit-Learn__en.srt | 17.33 KB | ||
| 006 PCA - Project Exercise Overview.mp4 | 52.77 MB | ||
| 006 PCA - Project Exercise Overview__en.srt | 11.87 KB | ||
| 007 PCA - Project Exercise Solution.mp4 | 119.45 MB | ||
| 007 PCA - Project Exercise Solution__en.srt | 25.72 KB | ||
| 33912190-digits.csv | 485.53 KB | ||
| 33912194-cancer-tumor-data-features.csv | 117.98 KB | ||
| 33912220-23-PCA-Principal-Component-Analysis.zip | 3.94 MB | ||
| 26 - Model Deployment | |||
| 001 Model Deployment Section Overview.mp4 | 4.16 MB | ||
| 001 Model Deployment Section Overview__en.srt | 3.49 KB | ||
| 002 Model Deployment Considerations.mp4 | 18.31 MB | ||
| 002 Model Deployment Considerations__en.srt | 10.57 KB | ||
| 003 Model Persistence.mp4 | 109.76 MB | ||
| 003 Model Persistence__en.srt | 3.07 KB | ||
| 003 Model Persistence_en.vtt | 28.11 KB | ||
| 004 Model Deployment as an API - General Overview.mp4 | 17.48 MB | ||
| 004 Model Deployment as an API - General Overview__en.srt | 11.61 KB | ||
| 005 Note on Upcoming Video.html | 249 B | ||
| 006 Model API - Creating the Script.mp4 | 67.27 MB | ||
| 006 Model API - Creating the Script__en.srt | 26.06 KB | ||
| 007 Testing the API.mp4 | 33.15 MB | ||
| 007 Testing the API__en.srt | 12.17 KB | ||
| Download Paid Udemy Courses For Free.url | 116 B | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| ▲ 517 total files | |||
2022 Python for Machine Learning & Data Science Masterclass
Learn about Data Science and Machine Learning with Python! Including Numpy, Pandas, Matplotlib, Scikit-Learn and more!
Udemy Link - https://www.udemy.com/course/python-for-machine-learning-data-science-masterclass/
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