[FreeCourseSite.com] Udemy - Regression Analysis in R for Machine Learning & Data Science
File List
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/005 Lab_ Machine Learning Models' Comparison & Best Model Selection.mp4 101.2 MB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/004 Lab_ Random Forest in R.mp4 100.1 MB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/002 Lab_ Polynomial regression in R.mp4 64.9 MB
- 05 More types of regression models/001 Lab_ Multiple linear regression - model estimation.mp4 60.1 MB
- 05 More types of regression models/005 ANOVA - Categorical variables with more than two levels in linear regressions.mp4 54.5 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/003 Your first linear regression model in R.mp4 53.3 MB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/002 Lab_ Decision Trees in R.mp4 52.0 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/001 Overview of Regression Analysis.mp4 49.2 MB
- 01 Introduction to the course, Machine Learning & Regression Analysis/002 Introduction to Regression Analysis.mp4 49.1 MB
- 03 R Crash Course - get started with R-programming in R-Studio/006 Lab_ data types and data structures in R.mp4 48.1 MB
- 02 Software used in this course R-Studio and Introduction to R/006 Lab_ Get started with R in RStudio.mp4 47.7 MB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/005 Lab_ Generalized additive models in R.mp4 47.5 MB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/004 Lab_ Spline regression in R.mp4 47.0 MB
- 05 More types of regression models/003 Lab_ Multiple linear regression with interaction.mp4 44.5 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/006 Lab_ Linear Regression Diagnostics.mp4 43.2 MB
- 02 Software used in this course R-Studio and Introduction to R/004 Lab_ Install R and RStudio in 2020.mp4 38.7 MB
- 03 R Crash Course - get started with R-programming in R-Studio/007 Vectors' operations in R.mp4 35.9 MB
- 01 Introduction to the course, Machine Learning & Regression Analysis/003 What is Machine Leraning and it's main types_.mp4 34.3 MB
- 03 R Crash Course - get started with R-programming in R-Studio/012 Read Data into R.mp4 31.9 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/010 Prediction model evaluation with data split_ out-of-sample RMSE.mp4 31.2 MB
- 02 Software used in this course R-Studio and Introduction to R/005 Introduction to RStudio Interface.mp4 30.7 MB
- 05 More types of regression models/004 Regression with Categorical Variables_ Dummy Coding Essentials in R.mp4 29.7 MB
- 03 R Crash Course - get started with R-programming in R-Studio/005 Overview of data types and data structures in R.mp4 27.2 MB
- 03 R Crash Course - get started with R-programming in R-Studio/011 Lab_ For Loops in R.mp4 24.8 MB
- 03 R Crash Course - get started with R-programming in R-Studio/010 Functions in R - overview.mp4 24.8 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/009 Predict with linear regression model & RMSE as in-sample error.mp4 24.4 MB
- 03 R Crash Course - get started with R-programming in R-Studio/002 Lab_ Installing Packages and Package Management in R.mp4 24.1 MB
- 01 Introduction to the course, Machine Learning & Regression Analysis/001 Introduction.mp4 21.4 MB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/003 Random Forest_ Theory.mp4 21.3 MB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/003 Lab_ Log transformation in R.mp4 19.0 MB
- 05 More types of regression models/002 Lab_ Multiple linear regression - prediction.mp4 18.8 MB
- 02 Software used in this course R-Studio and Introduction to R/003 How to install R and RStudio in 2020.mp4 16.7 MB
- 03 R Crash Course - get started with R-programming in R-Studio/009 Dataframes_ overview.mp4 16.7 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/002 Graphical Analysis of Regression Models.mp4 16.1 MB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/006 Your Final Project.mp4 15.0 MB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/001 Classification and Decision Trees (CART)_ Theory.mp4 13.3 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/004 Lab_ Correlation & Linear Regression Analysis in R.mp4 13.1 MB
- 02 Software used in this course R-Studio and Introduction to R/002 What is R and RStudio_.mp4 12.2 MB
- 03 R Crash Course - get started with R-programming in R-Studio/008 Data types and data structures_ Factors.mp4 9.3 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/005 How to know if the model is best fit for your data - theory.mp4 9.1 MB
- 03 R Crash Course - get started with R-programming in R-Studio/003 Variables in R and assigning Variables in R.mp4 9.0 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/007 Lab how to measure the linear model's fit_ AIC and BIC.mp4 8.6 MB
- 03 R Crash Course - get started with R-programming in R-Studio/004 Lab_ Variables in R and assigning Variables in R.mp4 7.6 MB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/008 Evaluation of Prediction Model Performance in Supervised Learning_ Regression.mp4 6.7 MB
- 01 Introduction to the course, Machine Learning & Regression Analysis/004 Overview of Machine Leraning in R.mp4 5.7 MB
- 03 R Crash Course - get started with R-programming in R-Studio/001 Introduction to Section 3.mp4 4.0 MB
- 02 Software used in this course R-Studio and Introduction to R/001 Introduction to Section 2.mp4 3.8 MB
- 03 R Crash Course - get started with R-programming in R-Studio/011 R Crash Course I_udemy_script.R 12.9 KB
- 05 More types of regression models/033 029_MultipleLinearRegression.R 3.8 KB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/047 027_ModelCompare.R 3.1 KB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/040 034_PolyRegression_LogTransform.R 2.7 KB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/041 035_SplineRegression.R 2.3 KB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/025 018_LM_diamonds.R 2.2 KB
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/039 033_PolynomialRegression.R 2.0 KB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/046 026_RandomForest.R 1.8 KB
- 05 More types of regression models/035 030_MultipleLinearRegression_interactions.R 1.5 KB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/028 020_LM_Diagnosis.R 1.4 KB
- 07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more/044 025_DecisionTress.R 1.2 KB
- 05 More types of regression models/037 032_ANOVA.R 1.2 KB
- 05 More types of regression models/036 031_DummyVariables.R 1.1 KB
- 04 Linear Regression Analysis for Supervised Machine Learning in R/032 022_RegressionModelValidation.R 875 bytes
- 04 Linear Regression Analysis for Supervised Machine Learning in R/031 019_RMSE_LM.R 827 bytes
- 04 Linear Regression Analysis for Supervised Machine Learning in R/026 020_CorrelationLinear.R 785 bytes
- 04 Linear Regression Analysis for Supervised Machine Learning in R/029 021_AIC.R 543 bytes
- 06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs/042 036_GAM.R 441 bytes
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