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[FreeCoursesOnline.Me] [Packt] Regression Analysis for Statistics and Machine Learning in R [FCO]
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[FreeCoursesOnline.Me] [Packt] Regression Analysis for Statistics and Machine Learning in R [FCO]
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文件列表
1.Get Started with Practical Regression Analysis in R/01.INTRODUCTION TO THE COURSE - The Key Concepts and Software Tools.mp4
121.2 MB
7.Working with Non-Parametric and Non-Linear Data/55.ML Model Selection.mp4
107.1 MB
6.Generalized Linear Models (GLMs)/45.Goodness of fit testing.mp4
91.4 MB
1.Get Started with Practical Regression Analysis in R/02.Difference Between Statistical Analysis & Machine Learning.mp4
75.6 MB
1.Get Started with Practical Regression Analysis in R/07.Basic Exploratory Data Analysis in R.mp4
58.3 MB
1.Get Started with Practical Regression Analysis in R/04.Reading in Data with R.mp4
52.2 MB
1.Get Started with Practical Regression Analysis in R/05.Data Cleaning with R.mp4
47.0 MB
6.Generalized Linear Models (GLMs)/41.Logistic regression.mp4
46.6 MB
7.Working with Non-Parametric and Non-Linear Data/48.Generalized Additive Models (GAMs) in R.mp4
41.9 MB
4.Variable & Model Selection/32.Evaluate Regression Model Performance.mp4
41.6 MB
4.Variable & Model Selection/29.Select the Most Suitable OLS Regression Model.mp4
40.7 MB
6.Generalized Linear Models (GLMs)/42.Logistic Regression for Binary Response Variable.mp4
33.2 MB
2.Ordinary Least Square Regression Modelling/18.Multiple Linear regression with Interaction and Dummy Variables.mp4
31.7 MB
3.Deal with Multicollinearity in OLS Regression Models/23.Principal Component Regression in R.mp4
31.0 MB
1.Get Started with Practical Regression Analysis in R/06.Some More Data Cleaning with R.mp4
30.4 MB
3.Deal with Multicollinearity in OLS Regression Models/21.Identify Multicollinearity.mp4
30.1 MB
7.Working with Non-Parametric and Non-Linear Data/51.CART-Regression Trees in R.mp4
29.7 MB
Exercise Files/code_9781838987862.zip
29.3 MB
2.Ordinary Least Square Regression Modelling/09.OLS Regression- Theory.mp4
29.1 MB
2.Ordinary Least Square Regression Modelling/19.Some Basic Conditions that OLS Models Have to Fulfill.mp4
28.9 MB
7.Working with Non-Parametric and Non-Linear Data/50.Multivariate Adaptive Regression Splines (MARS).mp4
27.7 MB
2.Ordinary Least Square Regression Modelling/10.OLS-Implementation.mp4
26.8 MB
7.Working with Non-Parametric and Non-Linear Data/56.Conclusions to Section 7.mp4
26.1 MB
4.Variable & Model Selection/34.Identify the Contribution of Predictors in Explaining the Variation in Y.mp4
26.1 MB
5.Dealing with Other Violations of the OLS Regression Models/36.Data Transformations.mp4
24.2 MB
1.Get Started with Practical Regression Analysis in R/03.Getting Started with R and R Studio.mp4
23.3 MB
2.Ordinary Least Square Regression Modelling/14.Confidence Interval and OLS Regressions.mp4
22.3 MB
4.Variable & Model Selection/30.Select Model Subsets.mp4
22.1 MB
3.Deal with Multicollinearity in OLS Regression Models/25.Ridge Regression in R.mp4
22.0 MB
7.Working with Non-Parametric and Non-Linear Data/53.Random Forest(RF).mp4
21.5 MB
3.Deal with Multicollinearity in OLS Regression Models/24.Partial Least Square Regression in R.mp4
20.5 MB
4.Variable & Model Selection/31.Machine Learning Perspective on Evaluate Regression Model Accuracy.mp4
20.4 MB
5.Dealing with Other Violations of the OLS Regression Models/37.Robust Regression-Deal with Outliers.mp4
20.0 MB
7.Working with Non-Parametric and Non-Linear Data/47.Polynomial and Non-linear regression.mp4
19.8 MB
6.Generalized Linear Models (GLMs)/43.Multinomial Logistic Regression.mp4
19.1 MB
2.Ordinary Least Square Regression Modelling/11.More on Result Interpretations.mp4
18.9 MB
2.Ordinary Least Square Regression Modelling/17.Multiple Linear Regression.mp4
18.0 MB
7.Working with Non-Parametric and Non-Linear Data/49.Boosted GAM Regression.mp4
17.3 MB
6.Generalized Linear Models (GLMs)/44.Regression for Count Data.mp4
16.8 MB
2.Ordinary Least Square Regression Modelling/12.Confidence Interval-Theory.mp4
15.7 MB
5.Dealing with Other Violations of the OLS Regression Models/38.Dealing with Heteroscedasticity.mp4
15.6 MB
3.Deal with Multicollinearity in OLS Regression Models/22.Doing Regression Analyses with Correlated Predictor Variables.mp4
15.0 MB
6.Generalized Linear Models (GLMs)/40.What are GLMs.mp4
13.3 MB
3.Deal with Multicollinearity in OLS Regression Models/26.LASSO Regression.mp4
13.2 MB
7.Working with Non-Parametric and Non-Linear Data/52.Conditional Inference Trees.mp4
12.3 MB
4.Variable & Model Selection/28.Why Do Any Kind of Selection.mp4
12.2 MB
2.Ordinary Least Square Regression Modelling/15.Linear Regression without Intercept.mp4
9.6 MB
4.Variable & Model Selection/33.LASSO Regression for Variable Selection.mp4
9.5 MB
7.Working with Non-Parametric and Non-Linear Data/54.Gradient Boosting Regression.mp4
9.0 MB
2.Ordinary Least Square Regression Modelling/13.Calculate the Confidence Interval in R.mp4
8.5 MB
2.Ordinary Least Square Regression Modelling/20.Conclusions to Section 2.mp4
8.4 MB
2.Ordinary Least Square Regression Modelling/16.Implement ANOVA on OLS Regression.mp4
7.8 MB
6.Generalized Linear Models (GLMs)/46.Conclusions to Section 6.mp4
7.1 MB
3.Deal with Multicollinearity in OLS Regression Models/27.Conclusion to Section 3.mp4
6.3 MB
1.Get Started with Practical Regression Analysis in R/08.Conclusion to Section 1.mp4
5.6 MB
4.Variable & Model Selection/35.Conclusions to Section 4.mp4
4.7 MB
5.Dealing with Other Violations of the OLS Regression Models/39.Conclusions to Section 5.mp4
3.6 MB
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377 Bytes
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286 Bytes
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239 Bytes
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208 Bytes
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163 Bytes
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