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[FreeCoursesOnline.Me] [Packt] Regression Analysis for Statistics and Machine Learning in R [FCO]
magnet:?xt=urn:btih:46ccad14c58fc19493e0b01ec226202b0d9cc1c0&dn=[FreeCoursesOnline.Me] [Packt] Regression Analysis for Statistics and Machine Learning in R [FCO]
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Hash值:
46ccad14c58fc19493e0b01ec226202b0d9cc1c0
点击数:
196
文件大小:
1.45 GB
文件数量:
56
创建日期:
2020-1-21 05:15
最后访问:
2024-7-6 02:29
访问标签:
FreeCoursesOnline
Me
Packt
Regression
Analysis
for
Statistics
and
Machine
Learning
in
R
FCO
文件列表详情
1.Get Started with Practical Regression Analysis in R/01.INTRODUCTION TO THE COURSE - The Key Concepts and Software Tools.mp4 115.63 MB
1.Get Started with Practical Regression Analysis in R/02.Difference Between Statistical Analysis & Machine Learning.mp4 72.07 MB
1.Get Started with Practical Regression Analysis in R/03.Getting Started with R and R Studio.mp4 22.2 MB
1.Get Started with Practical Regression Analysis in R/04.Reading in Data with R.mp4 49.83 MB
1.Get Started with Practical Regression Analysis in R/05.Data Cleaning with R.mp4 44.79 MB
1.Get Started with Practical Regression Analysis in R/06.Some More Data Cleaning with R.mp4 28.97 MB
1.Get Started with Practical Regression Analysis in R/07.Basic Exploratory Data Analysis in R.mp4 55.59 MB
1.Get Started with Practical Regression Analysis in R/08.Conclusion to Section 1.mp4 5.33 MB
2.Ordinary Least Square Regression Modelling/09.OLS Regression- Theory.mp4 27.72 MB
2.Ordinary Least Square Regression Modelling/10.OLS-Implementation.mp4 25.54 MB
2.Ordinary Least Square Regression Modelling/11.More on Result Interpretations.mp4 18.01 MB
2.Ordinary Least Square Regression Modelling/12.Confidence Interval-Theory.mp4 14.98 MB
2.Ordinary Least Square Regression Modelling/13.Calculate the Confidence Interval in R.mp4 8.12 MB
2.Ordinary Least Square Regression Modelling/14.Confidence Interval and OLS Regressions.mp4 21.31 MB
2.Ordinary Least Square Regression Modelling/15.Linear Regression without Intercept.mp4 9.17 MB
2.Ordinary Least Square Regression Modelling/16.Implement ANOVA on OLS Regression.mp4 7.48 MB
2.Ordinary Least Square Regression Modelling/17.Multiple Linear Regression.mp4 17.19 MB
2.Ordinary Least Square Regression Modelling/18.Multiple Linear regression with Interaction and Dummy Variables.mp4 30.27 MB
2.Ordinary Least Square Regression Modelling/19.Some Basic Conditions that OLS Models Have to Fulfill.mp4 27.59 MB
2.Ordinary Least Square Regression Modelling/20.Conclusions to Section 2.mp4 7.97 MB
3.Deal with Multicollinearity in OLS Regression Models/21.Identify Multicollinearity.mp4 28.71 MB
3.Deal with Multicollinearity in OLS Regression Models/22.Doing Regression Analyses with Correlated Predictor Variables.mp4 14.29 MB
3.Deal with Multicollinearity in OLS Regression Models/23.Principal Component Regression in R.mp4 29.6 MB
3.Deal with Multicollinearity in OLS Regression Models/24.Partial Least Square Regression in R.mp4 19.58 MB
3.Deal with Multicollinearity in OLS Regression Models/25.Ridge Regression in R.mp4 20.94 MB
3.Deal with Multicollinearity in OLS Regression Models/26.LASSO Regression.mp4 12.58 MB
3.Deal with Multicollinearity in OLS Regression Models/27.Conclusion to Section 3.mp4 6.05 MB
4.Variable & Model Selection/28.Why Do Any Kind of Selection.mp4 11.61 MB
4.Variable & Model Selection/29.Select the Most Suitable OLS Regression Model.mp4 38.77 MB
4.Variable & Model Selection/30.Select Model Subsets.mp4 21.11 MB
4.Variable & Model Selection/31.Machine Learning Perspective on Evaluate Regression Model Accuracy.mp4 19.43 MB
4.Variable & Model Selection/32.Evaluate Regression Model Performance.mp4 39.65 MB
4.Variable & Model Selection/33.LASSO Regression for Variable Selection.mp4 9.08 MB
4.Variable & Model Selection/34.Identify the Contribution of Predictors in Explaining the Variation in Y.mp4 24.88 MB
4.Variable & Model Selection/35.Conclusions to Section 4.mp4 4.46 MB
5.Dealing with Other Violations of the OLS Regression Models/36.Data Transformations.mp4 23.11 MB
5.Dealing with Other Violations of the OLS Regression Models/37.Robust Regression-Deal with Outliers.mp4 19.1 MB
5.Dealing with Other Violations of the OLS Regression Models/38.Dealing with Heteroscedasticity.mp4 14.89 MB
5.Dealing with Other Violations of the OLS Regression Models/39.Conclusions to Section 5.mp4 3.44 MB
6.Generalized Linear Models (GLMs)/40.What are GLMs.mp4 12.71 MB
6.Generalized Linear Models (GLMs)/41.Logistic regression.mp4 44.41 MB
6.Generalized Linear Models (GLMs)/42.Logistic Regression for Binary Response Variable.mp4 31.67 MB
6.Generalized Linear Models (GLMs)/43.Multinomial Logistic Regression.mp4 18.2 MB
6.Generalized Linear Models (GLMs)/44.Regression for Count Data.mp4 16.06 MB
6.Generalized Linear Models (GLMs)/45.Goodness of fit testing.mp4 87.21 MB
6.Generalized Linear Models (GLMs)/46.Conclusions to Section 6.mp4 6.73 MB
7.Working with Non-Parametric and Non-Linear Data/47.Polynomial and Non-linear regression.mp4 18.86 MB
7.Working with Non-Parametric and Non-Linear Data/48.Generalized Additive Models (GAMs) in R.mp4 39.93 MB
7.Working with Non-Parametric and Non-Linear Data/49.Boosted GAM Regression.mp4 16.5 MB
7.Working with Non-Parametric and Non-Linear Data/50.Multivariate Adaptive Regression Splines (MARS).mp4 26.45 MB
7.Working with Non-Parametric and Non-Linear Data/51.CART-Regression Trees in R.mp4 28.33 MB
7.Working with Non-Parametric and Non-Linear Data/52.Conditional Inference Trees.mp4 11.71 MB
7.Working with Non-Parametric and Non-Linear Data/53.Random Forest(RF).mp4 20.49 MB
7.Working with Non-Parametric and Non-Linear Data/54.Gradient Boosting Regression.mp4 8.61 MB
7.Working with Non-Parametric and Non-Linear Data/55.ML Model Selection.mp4 102.18 MB
7.Working with Non-Parametric and Non-Linear Data/56.Conclusions to Section 7.mp4 24.93 MB
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