Machine Learning 2021 Practical Regression Analysis in | 924E9693AB7B1B83B24DF2D118EA60180D756348

Machine Learning 2021 Practical Regression Analysis in

Name	Machine Learning 2021 Practical Regression Analysis in R	DOWNLOAD Copy Link
Total Size	1.6 GB
Total Files	168
Hash	924E9693AB7B1B83B24DF2D118EA60180D756348

/.../7. Non-Parametric Regression Analysis in R Random Forest, Decision Trees and more/
6. Lab Machine Learning Models' Comparison & Best Model Selection.mp4	106.2 MB
6. Lab Machine Learning Models' Comparison & Best Model Selection.srt	14.5 KB
4. Lab Random Forest in R.srt	12.5 KB
2. Lab Decision Trees in R.srt	7.3 KB
1. Classification and Decision Trees (CART) Theory.srt	4.7 KB
3. Random Forest Theory.srt	4.5 KB
4. Lab Random Forest in R.mp4	105.0 MB
6.1 027_ModelCompare.R	3.1 KB
7. Your Final Project.srt	2.4 KB
4.1 026_RandomForest.R	1.8 KB
2.1 025_DecisionTress.R	1.2 KB
5. Parametrise Random Forest model.html	0.2 KB
2. Lab Decision Trees in R.mp4	54.5 MB
3. Random Forest Theory.mp4	22.3 MB
7. Your Final Project.mp4	15.8 MB
1. Classification and Decision Trees (CART) Theory.mp4	14.0 MB
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TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../3. R Crash Course - get started with R-programming in R-Studio/
1.1 R Crash Course I_udemy_script.R	13.3 KB
6. Lab data types and data structures in R.srt	9.0 KB
5. Overview of data types and data structures in R.srt	8.4 KB
7. Vectors' operations in R.srt	7.4 KB
1. Introduction to Section 3.srt	1.2 KB
3. Variables in R and assigning Variables in R.srt	2.6 KB
4. Lab Variables in R and assigning Variables in R.srt	1.8 KB
12. Read Data into R.srt	4.9 KB
2. Lab Installing Packages and Package Management in R.srt	4.6 KB
8. Data types and data structures Factors.srt	2.7 KB
9. Dataframes overview.srt	4.1 KB
11. Lab For Loops in R.srt	4.1 KB
10. Functions in R - overview.srt	4.1 KB
6. Lab data types and data structures in R.mp4	50.4 MB
7. Vectors' operations in R.mp4	37.7 MB
12. Read Data into R.mp4	33.5 MB
5. Overview of data types and data structures in R.mp4	28.5 MB
11. Lab For Loops in R.mp4	26.0 MB
10. Functions in R - overview.mp4	26.0 MB
2. Lab Installing Packages and Package Management in R.mp4	25.3 MB
9. Dataframes overview.mp4	17.5 MB
8. Data types and data structures Factors.mp4	9.8 MB
3. Variables in R and assigning Variables in R.mp4	9.4 MB
4. Lab Variables in R and assigning Variables in R.mp4	8.0 MB
1. Introduction to Section 3.mp4	4.2 MB
/.../1. Introduction to the course, Machine Learning & Regression Analysis/
2. Introduction to Regression Analysis.srt	12.8 KB
3. Introduction to Regression Analysis.html	0.2 KB
4. What is Machine Leraning and it's main types.srt	10.1 KB
5. Overview of Machine Leraning in R.srt	2.1 KB
6. Machine Learning Types.html	0.2 KB
1. Introduction.srt	3.1 KB
2. Introduction to Regression Analysis.mp4	51.5 MB
4. What is Machine Leraning and it's main types.mp4	36.0 MB
1. Introduction.mp4	22.5 MB
5. Overview of Machine Leraning in R.mp4	5.9 MB
/.../4. Linear Regression Analysis for Supervised Machine Learning in R/
1. Overview of Regression Analysis.srt	12.8 KB
4. Your first linear regression model in R.srt	8.7 KB
7. Lab Linear Regression Diagnostics.srt	7.4 KB
3. Graphical Analysis of Regression Models.srt	6.6 KB
11. Prediction model evaluation with data split out-of-sample RMSE.srt	5.2 KB
10. Predict with linear regression model & RMSE as in-sample error.srt	4.6 KB
9. Evaluation of Prediction Model Performance in Supervised Learning Regression.srt	2.9 KB
2. Overview of Regression Analysis.html	0.2 KB
6. How to know if the model is best fit for your data - theory.srt	2.8 KB
4.1 018_LM_diamonds.R	2.3 KB
5. Lab Correlation & Linear Regression Analysis in R.srt	2.5 KB
5.1 020_CorrelationLinear.R	0.8 KB
8. Lab how to measure the linear model's fit AIC and BIC.srt	1.8 KB
7.1 020_LM_Diagnosis.R	1.4 KB
8.1 021_AIC.R	0.5 KB
11.1 022_RegressionModelValidation.R	0.9 KB
10.1 019_RMSE_LM.R	0.8 KB
4. Your first linear regression model in R.mp4	55.9 MB
1. Overview of Regression Analysis.mp4	51.6 MB
7. Lab Linear Regression Diagnostics.mp4	45.3 MB
11. Prediction model evaluation with data split out-of-sample RMSE.mp4	32.7 MB
10. Predict with linear regression model & RMSE as in-sample error.mp4	25.6 MB
3. Graphical Analysis of Regression Models.mp4	16.9 MB
5. Lab Correlation & Linear Regression Analysis in R.mp4	13.7 MB
6. How to know if the model is best fit for your data - theory.mp4	9.6 MB
8. Lab how to measure the linear model's fit AIC and BIC.mp4	9.0 MB
9. Evaluation of Prediction Model Performance in Supervised Learning Regression.mp4	7.1 MB
/.../6. Non-Linear Regression Analysis in R Polynomial & Spline regression, GAMs/
2. Lab Polynomial regression in R.srt	11.0 KB
4. Lab Spline regression in R.srt	7.1 KB
5. Lab Generalized additive models in R.srt	6.9 KB
1. Nonlinear Regression Essentials in R Polynomial and Spline Regression Models.srt	6.0 KB
3. Lab Log transformation in R.srt	3.5 KB
3.1 034_PolyRegression_LogTransform.R	2.8 KB
4.1 035_SplineRegression.R	2.3 KB
2.1 033_PolynomialRegression.R	2.1 KB
5.1 036_GAM.R	0.4 KB
2. Lab Polynomial regression in R.mp4	68.1 MB
5. Lab Generalized additive models in R.mp4	49.8 MB
4. Lab Spline regression in R.mp4	49.2 MB
1. Nonlinear Regression Essentials in R Polynomial and Spline Regression Models.mp4	27.3 MB
3. Lab Log transformation in R.mp4	19.9 MB
/.../5. More types of regression models/
5. ANOVA - Categorical variables with more than two levels in linear regressions.srt	10.0 KB
1. Lab Multiple linear regression - model estimation.srt	9.4 KB
3. Lab Multiple linear regression with interaction.srt	8.9 KB
4. Regression with Categorical Variables Dummy Coding Essentials in R.srt	5.9 KB
1.1 029_MultipleLinearRegression.R	3.9 KB
2. Lab Multiple linear regression - prediction.srt	3.9 KB
3.1 030_MultipleLinearRegression_interactions.R	1.5 KB
5.1 032_ANOVA.R	1.2 KB
4.1 031_DummyVariables.R	1.1 KB
1. Lab Multiple linear regression - model estimation.mp4	63.1 MB
5. ANOVA - Categorical variables with more than two levels in linear regressions.mp4	57.2 MB
3. Lab Multiple linear regression with interaction.mp4	46.7 MB
4. Regression with Categorical Variables Dummy Coding Essentials in R.mp4	31.1 MB
2. Lab Multiple linear regression - prediction.mp4	19.7 MB
/.../2. Software used in this course R-Studio and Introduction to R/
1. Introduction to Section 2.srt	0.6 KB
6. Lab Get started with R in RStudio.srt	9.7 KB
5. Introduction to RStudio Interface.srt	8.5 KB
7. What is the latest version of RStudio and R.html	0.2 KB
4. Lab Install R and RStudio in 2020.srt	6.3 KB
3. How to install R and RStudio in 2020.srt	4.2 KB
2. What is R and RStudio.srt	3.1 KB
6. Lab Get started with R in RStudio.mp4	50.0 MB
4. Lab Install R and RStudio in 2020.mp4	40.6 MB
5. Introduction to RStudio Interface.mp4	32.2 MB
3. How to install R and RStudio in 2020.mp4	17.5 MB
2. What is R and RStudio.mp4	12.8 MB
1. Introduction to Section 2.mp4	3.9 MB
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Total files 168