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Download Machine Learning Basics Practical Linear Regression in R

Machine Learning Basics Practical Linear Regression in

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Machine Learning Basics Practical Linear Regression in R

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788.3 MB

Total Files

84

Last Seen

2024-11-09 23:27

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A4E88F0F9DC88BC2E6065D1AAEF6018F25134BBD

/.../4. More types of linear regression models in R/

6. GLM Preview Logistic Regression Model & Accuracy Assessment.mp4

86.9 MB

6. GLM Preview Logistic Regression Model & Accuracy Assessment.srt

10.3 KB

5. ANOVA - Categorical variables with more than two levels in linear regressions.srt

10.0 KB

1. Lab Multiple linear regression - model estimation in R.srt

9.4 KB

3. Lab Multiple linear regression with interaction in R.srt

8.9 KB

8. Lab Receiver operating characteristic (ROC) curve and AUC.srt

6.7 KB

4. Lab 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 in R.srt

3.9 KB

6.1 023_ClassificationAccuracy.R

2.1 KB

7. Compare the model accuracy (or any other metric) using thresholds of 0.1 and 0.9..html

0.2 KB

8.1 024_ROC.R

1.5 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

9. Your final coding exercise.html

0.2 KB

1. Lab Multiple linear regression - model estimation in R.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 in R.mp4

46.7 MB

8. Lab Receiver operating characteristic (ROC) curve and AUC.mp4

38.5 MB

4. Lab Regression with Categorical Variables Dummy Coding Essentials in R.mp4

31.1 MB

2. Lab Multiple linear regression - prediction in R.mp4

19.8 MB

/

TutsNode.com.txt

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[TGx]Downloaded from torrentgalaxy.to .txt

0.6 KB

/1. Introduction/

2. Introduction to Regression Analysis and Linear Regression.srt

12.8 KB

1. Introduction.srt

2.9 KB

4. What is Machine Leraning and it's main types.srt

11.5 KB

3. Introduction to Regression Analysis.html

0.2 KB

5. Machine Learning Types.html

0.2 KB

2. Introduction to Regression Analysis and Linear Regression.mp4

51.5 MB

4. What is Machine Leraning and it's main types.mp4

49.1 MB

1. Introduction.mp4

18.1 MB

/.../2. Software used in this course R-Studio and Introduction to R/

3. Lab Get started with R in RStudio.srt

9.7 KB

4. What is the latest version of RStudio and R.html

0.2 KB

2. How to install R and RStudio in 2020.srt

6.3 KB

1. What is R and RStudio.srt

3.1 KB

3. Lab Get started with R in RStudio.mp4

50.0 MB

2. How to install R and RStudio in 2020.mp4

40.6 MB

1. What is R and RStudio.mp4

12.8 MB

/.../3. Linear Regression in R/

2. Lab your first linear regression model.srt

8.7 KB

5. Linear Regression Diagnostics.srt

7.4 KB

1. Getting started with linear regression.srt

6.6 KB

9. Prediction model evaluation with data split out-of-sample RMSE.srt

5.2 KB

8. Lab Predict with linear regression model & RMSE as in-sample error.srt

4.6 KB

2.1 018_LM_diamonds.R

2.3 KB

3. Correlation in Regression Analysis in R Lab.srt

2.5 KB

3.1 020_CorrelationLinear.R

0.8 KB

4. How to know if the model is best fit for your data - An overview.srt

2.8 KB

5.1 020_LM_Diagnosis.R

1.4 KB

6. AIC and BIC.srt

1.8 KB

6.1 021_AIC.R

0.5 KB

7. Evaluation of Performance of Regression-based Prediction Model.srt

2.9 KB

8.1 019_RMSE_LM.R

0.8 KB

9.1 022_RegressionModelValidation.R

0.9 KB

2. Lab your first linear regression model.mp4

55.9 MB

5. Linear Regression Diagnostics.mp4

45.3 MB

9. Prediction model evaluation with data split out-of-sample RMSE.mp4

32.7 MB

8. Lab Predict with linear regression model & RMSE as in-sample error.mp4

25.5 MB

1. Getting started with linear regression.mp4

16.9 MB

3. Correlation in Regression Analysis in R Lab.mp4

13.7 MB

4. How to know if the model is best fit for your data - An overview.mp4

9.6 MB

6. AIC and BIC.mp4

9.0 MB

7. Evaluation of Performance of Regression-based Prediction Model.mp4

7.1 MB

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Total files 84


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