| 01 Introduction | |||
| 001 Welcome to the Course!.en.srt | 17.62 KB | ||
| 001 Welcome to the Course!.mp4 | 128.49 MB | ||
| 002 Course Materials.html | 1.32 KB | ||
| external-assets-links.txt | 231 B | ||
| 02 Setting up Environment - R and R Studio | |||
| 001 Installing R.en.srt | 8.89 KB | ||
| 001 Installing R.mp4 | 74.23 MB | ||
| 002 Installing R Studio.en.srt | 10.84 KB | ||
| 002 Installing R Studio.mp4 | 90.03 MB | ||
| external-assets-links.txt | 120 B | ||
| 03 Installing Libraries | |||
| 001 Installing Libraries.en.srt | 14.02 KB | ||
| 001 Installing Libraries.mp4 | 140.74 MB | ||
| 002 Loading Libraries.en.srt | 2.77 KB | ||
| 002 Loading Libraries.mp4 | 27.06 MB | ||
| 003 Let's start!.en.srt | 995 B | ||
| 003 Let's start!.mp4 | 6.89 MB | ||
| 04 Manipulating Data with Dplyr | |||
| 001 Intro to Dplyr and Tibble Data Structure.en.srt | 7.82 KB | ||
| 001 Intro to Dplyr and Tibble Data Structure.mp4 | 38.82 MB | ||
| 002 Filter and Pipe Format.en.srt | 9 KB | ||
| 002 Filter and Pipe Format.mp4 | 51.64 MB | ||
| 003 Glimpse and Lists as Columns.en.srt | 4.64 KB | ||
| 003 Glimpse and Lists as Columns.mp4 | 32.98 MB | ||
| 004 Function Encapsulation and Multiple Arguments.en.srt | 4.42 KB | ||
| 004 Function Encapsulation and Multiple Arguments.mp4 | 27.74 MB | ||
| 005 Arrange and Mutate.en.srt | 10 KB | ||
| 005 Arrange and Mutate.mp4 | 74.83 MB | ||
| 006 Select and Distinct.en.srt | 6.31 KB | ||
| 006 Select and Distinct.mp4 | 36.96 MB | ||
| 007 Sample_N and Sample_Frac.en.srt | 4.23 KB | ||
| 007 Sample_N and Sample_Frac.mp4 | 30.43 MB | ||
| 008 Summarize and Group By.en.srt | 4.45 KB | ||
| 008 Summarize and Group By.mp4 | 29.82 MB | ||
| 009 Joining Dataframes.en.srt | 8.82 KB | ||
| 009 Joining Dataframes.mp4 | 61.68 MB | ||
| 010 Small Typo.html | 1.07 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 05 Linear Regression | |||
| 001 Linear Regression - Introduction.en.srt | 1.76 KB | ||
| 001 Linear Regression - Introduction.mp4 | 12.76 MB | ||
| 002 Loading the Data into R.en.srt | 5.67 KB | ||
| 002 Loading the Data into R.mp4 | 33.02 MB | ||
| 003 Plotting Feature (Age) and Target (Income) Variables.en.srt | 5.64 KB | ||
| 003 Plotting Feature (Age) and Target (Income) Variables.mp4 | 34.35 MB | ||
| 004 Fitting a Random Line.en.srt | 6.72 KB | ||
| 004 Fitting a Random Line.mp4 | 39.57 MB | ||
| 005 Adjusting the Weight of our Linear Model.en.srt | 4.85 KB | ||
| 005 Adjusting the Weight of our Linear Model.mp4 | 29.83 MB | ||
| 006 Training our First Linear Model.en.srt | 6.84 KB | ||
| 006 Training our First Linear Model.mp4 | 40.11 MB | ||
| 007 Linear Regression Evaluation.en.srt | 18.01 KB | ||
| 007 Linear Regression Evaluation.mp4 | 108.62 MB | ||
| 008 Linear Regression Closed Form Solution.en.srt | 17.38 KB | ||
| 008 Linear Regression Closed Form Solution.mp4 | 82 MB | ||
| 009 Gradient Descent Intuition - Part 1.en.srt | 20.74 KB | ||
| 009 Gradient Descent Intuition - Part 1.mp4 | 130.75 MB | ||
| 010 Gradient Descent Intuition - Part 2.en.srt | 12.66 KB | ||
| 010 Gradient Descent Intuition - Part 2.mp4 | 84.22 MB | ||
| 011 Visualizing Gradient Descent.en.srt | 12.58 KB | ||
| 011 Visualizing Gradient Descent.mp4 | 70.95 MB | ||
| 012 Multivariate Linear Regression.en.srt | 19.41 KB | ||
| 012 Multivariate Linear Regression.mp4 | 109.49 MB | ||
| 06 Classification Problems and Logistic Regression | |||
| 001 Classification Problems - Introduction.en.srt | 2.73 KB | ||
| 001 Classification Problems - Introduction.mp4 | 10.11 MB | ||
| 002 Classification Problems Intuition - Why Linear Regression is unfit.en.srt | 15.63 KB | ||
| 002 Classification Problems Intuition - Why Linear Regression is unfit.mp4 | 81.78 MB | ||
| 003 Calculating Sigmoid Function and Fitting a Logistic Regression.en.srt | 10 KB | ||
| 003 Calculating Sigmoid Function and Fitting a Logistic Regression.mp4 | 56.35 MB | ||
| 004 Summary of Logistic Regression and Accuracy.en.srt | 10.96 KB | ||
| 004 Summary of Logistic Regression and Accuracy.mp4 | 69.32 MB | ||
| 005 Log-Loss Function Intuition.en.srt | 19.41 KB | ||
| 005 Log-Loss Function Intuition.mp4 | 93.9 MB | ||
| 006 Gradient Descent Intuition - Classification.en.srt | 12.48 KB | ||
| 006 Gradient Descent Intuition - Classification.mp4 | 74.48 MB | ||
| 007 Visualizing Log-Loss in 3 Dimensions.en.srt | 13.3 KB | ||
| 007 Visualizing Log-Loss in 3 Dimensions.mp4 | 79.69 MB | ||
| 07 Model Evaluation and Selection | |||
| 001 Model Evaluation and Selection - Introduction.en.srt | 3.13 KB | ||
| 001 Model Evaluation and Selection - Introduction.mp4 | 7.84 MB | ||
| 002 Example of a High Bias Model.en.srt | 15.18 KB | ||
| 002 Example of a High Bias Model.mp4 | 88.85 MB | ||
| 003 Example of a High Variance Model.en.srt | 18.86 KB | ||
| 003 Example of a High Variance Model.mp4 | 132.19 MB | ||
| 004 Evaluating the Model on Unseen Data.en.srt | 19.55 KB | ||
| 004 Evaluating the Model on Unseen Data.mp4 | 134.27 MB | ||
| 005 Randomized Train and Test Split.en.srt | 16.84 KB | ||
| 005 Randomized Train and Test Split.mp4 | 73.17 MB | ||
| 006 Performance across Training and Test Data.en.srt | 20.75 KB | ||
| 006 Performance across Training and Test Data.mp4 | 127.72 MB | ||
| 007 Regression Metrics - Plotting the Residuals.en.srt | 17.91 KB | ||
| 007 Regression Metrics - Plotting the Residuals.mp4 | 104.4 MB | ||
| 008 Regression Metrics - MSE, MAE and RMSE.en.srt | 10.11 KB | ||
| 008 Regression Metrics - MSE, MAE and RMSE.mp4 | 61.29 MB | ||
| 009 Regression Metrics - R-Square Breakdown and MAPE.en.srt | 10.64 KB | ||
| 009 Regression Metrics - R-Square Breakdown and MAPE.mp4 | 61.94 MB | ||
| 010 Classification Metrics - Fitting Logistic Regression and Confusion Matrix Intro.en.srt | 16.64 KB | ||
| 010 Classification Metrics - Fitting Logistic Regression and Confusion Matrix Intro.mp4 | 90.31 MB | ||
| 011 Classification Metrics - TP, FP, TN, FN.en.srt | 4.8 KB | ||
| 011 Classification Metrics - TP, FP, TN, FN.mp4 | 27.89 MB | ||
| 012 Classification Metrics - Precision, Recall and F-Score.en.srt | 8.2 KB | ||
| 012 Classification Metrics - Precision, Recall and F-Score.mp4 | 40.68 MB | ||
| 013 Classification Metrics - Building ROC Curve.en.srt | 14.3 KB | ||
| 013 Classification Metrics - Building ROC Curve.mp4 | 83 MB | ||
| 014 Classification Metrics - ROCR Package and Area Under the Curve.en.srt | 9.15 KB | ||
| 014 Classification Metrics - ROCR Package and Area Under the Curve.mp4 | 45.65 MB | ||
| 08 Tree Based Models - Decision Trees | |||
| 001 Classification Trees - Problem Evaluation and Fitting a Logistic Regression.en.srt | 12.54 KB | ||
| 001 Classification Trees - Problem Evaluation and Fitting a Logistic Regression.mp4 | 69.27 MB | ||
| 002 Classification Trees - First Split and Gini Impurity Concept.en.srt | 18.15 KB | ||
| 002 Classification Trees - First Split and Gini Impurity Concept.mp4 | 112.5 MB | ||
| 003 Classification Trees - Finding the Best Split with Minimum Gini Impurity.en.srt | 11.64 KB | ||
| 003 Classification Trees - Finding the Best Split with Minimum Gini Impurity.mp4 | 82.77 MB | ||
| 004 Classification Trees - Fitting a Decision Tree using RPart.en.srt | 7.49 KB | ||
| 004 Classification Trees - Fitting a Decision Tree using RPart.mp4 | 43.42 MB | ||
| 005 Classification Trees - Adding more Thresholds and Visualizing Classification.en.srt | 7.97 KB | ||
| 005 Classification Trees - Adding more Thresholds and Visualizing Classification.mp4 | 45.41 MB | ||
| 006 Classification Trees - Tweaking Hyperparameters and Checking Accuracy.en.srt | 6.15 KB | ||
| 006 Classification Trees - Tweaking Hyperparameters and Checking Accuracy.mp4 | 36.16 MB | ||
| 007 Regression Trees - Intuition.en.srt | 15.47 KB | ||
| 007 Regression Trees - Intuition.mp4 | 84.81 MB | ||
| 008 Regression Trees - Calculating Residual Sum of Squares.en.srt | 6.28 KB | ||
| 008 Regression Trees - Calculating Residual Sum of Squares.mp4 | 38.52 MB | ||
| 009 Regression Trees - Finding the Best Split with Residual Sum of Squares.en.srt | 7.86 KB | ||
| 009 Regression Trees - Finding the Best Split with Residual Sum of Squares.mp4 | 54.97 MB | ||
| 010 Regression Trees - Fitting the Algorithm.en.srt | 8.53 KB | ||
| 010 Regression Trees - Fitting the Algorithm.mp4 | 52.05 MB | ||
| 011 Regression Trees - Comparing between Tree and Linear Model.en.srt | 17.57 KB | ||
| 011 Regression Trees - Comparing between Tree and Linear Model.mp4 | 119.73 MB | ||
| 09 Tree Based Models - Random Forests | |||
| 001 Random Forest Intuition and Subsetting Data.en.srt | 10.41 KB | ||
| 001 Random Forest Intuition and Subsetting Data.mp4 | 49.32 MB | ||
| 002 Fitting Different Decision Trees.en.srt | 12.81 KB | ||
| 002 Fitting Different Decision Trees.mp4 | 85.88 MB | ||
| 003 Building a Random Forest from Scratch with Three Estimators.en.srt | 10.88 KB | ||
| 003 Building a Random Forest from Scratch with Three Estimators.mp4 | 73.81 MB | ||
| 004 Measuring the Accuracy of Each Trees and of the Ensemble Average.en.srt | 4.69 KB | ||
| 004 Measuring the Accuracy of Each Trees and of the Ensemble Average.mp4 | 35.57 MB | ||
| 005 Random Forest - R Package Implementation.en.srt | 8.37 KB | ||
| 005 Random Forest - R Package Implementation.mp4 | 48.16 MB | ||
| 10 Data Science Project - Kaggle Taxi Trip Duration | |||
| 001 Data Science Project - Taxi Trip Duration Project - Introduction.en.srt | 5.64 KB | ||
| 001 Data Science Project - Taxi Trip Duration Project - Introduction.mp4 | 21.06 MB | ||
| 002 Exploratory Data Analysis - Loading Taxi Trip and Analyzing Outliers.en.srt | 12.02 KB | ||
| 002 Exploratory Data Analysis - Loading Taxi Trip and Analyzing Outliers.mp4 | 68.78 MB | ||
| 003 Exploratory Data Analysis - Removing Outliers.en.srt | 15.46 KB | ||
| 003 Exploratory Data Analysis - Removing Outliers.mp4 | 106.4 MB | ||
| 004 Feature Engineering - Time Based Features.en.srt | 15.69 KB | ||
| 004 Feature Engineering - Time Based Features.mp4 | 89.19 MB | ||
| 005 Feature Engineering - Visualizing Trip Duration per Feature.en.srt | 8.67 KB | ||
| 005 Feature Engineering - Visualizing Trip Duration per Feature.mp4 | 62.52 MB | ||
| 006 Feature Engineering - Building Location Based Features (Manhattan and Euclidean).en.srt | 12.67 KB | ||
| 006 Feature Engineering - Building Location Based Features (Manhattan and Euclidean).mp4 | 89.06 MB | ||
| 007 Feature Engineering - Visualizing Correlation and Adding Features to our table.en.srt | 15.5 KB | ||
| 007 Feature Engineering - Visualizing Correlation and Adding Features to our table.mp4 | 111.25 MB | ||
| 008 Feature Engineering - Creating Weekday feature and Building Data Pipeline.en.srt | 16.74 KB | ||
| 008 Feature Engineering - Creating Weekday feature and Building Data Pipeline.mp4 | 108.24 MB | ||
| 009 Modelling - Preparing Data for Modelling.en.srt | 14.2 KB | ||
| 009 Modelling - Preparing Data for Modelling.mp4 | 89.19 MB | ||
| 010 Modelling - Fitting Linear Regression.en.srt | 10.31 KB | ||
| 010 Modelling - Fitting Linear Regression.mp4 | 69.39 MB | ||
| 011 Modelling - Training a Random Forest.en.srt | 18.44 KB | ||
| 011 Modelling - Training a Random Forest.mp4 | 112.62 MB | ||
| 012 Modelling - Caret Implementation and API.en.srt | 9.23 KB | ||
| 012 Modelling - Caret Implementation and API.mp4 | 60.13 MB | ||
| 013 Modelling - Building Custom Experiments _ Hyperparameter Tuning.en.srt | 7.96 KB | ||
| 013 Modelling - Building Custom Experiments _ Hyperparameter Tuning.mp4 | 56.93 MB | ||
| 014 Modelling - Evaluating Best Model.en.srt | 6.75 KB | ||
| 014 Modelling - Evaluating Best Model.mp4 | 49.22 MB | ||
| 015 Evaluating - Preparing New Data for Scoring.en.srt | 23.66 KB | ||
| 015 Evaluating - Preparing New Data for Scoring.mp4 | 141.5 MB | ||
| 016 Evaluating - Scoring New Data and Submitting do Kaggle.en.srt | 9.85 KB | ||
| 016 Evaluating - Scoring New Data and Submitting do Kaggle.mp4 | 61.69 MB | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| 11 Thank you! | |||
| 001 Bonus Lecture - Other Courses.html | 1.72 KB | ||
| 002 Detailed Feedback.html | 1.19 KB | ||
| 003 Final Notes.en.srt | 1.86 KB | ||
| 003 Final Notes.mp4 | 13.8 MB | ||
| Download Paid Udemy Courses For Free.url | 116 B | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B |
R for Data Science: Your First Step as a Data Scientist
Learn Data Science and Machine Learning (ML) with R Studio and submit your first Kaggle Project
Udemy Link - https://www.udemy.com/course/r-for-data-science-first-step-data-scientist/
Please seed as much as you can!
| torrent name | size | uploader | age | seed | leech |
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| 803.9 MB | freecoursewb | 4 weeks | 15 | 15 | |
| 1.4 GB | freecoursewb | 9 months | 0 | 0 | |
| 1.5 GB | freecoursewb | 1 year | 0 | 0 | |
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