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[UdemyCourseDownloader] Regression Analysis For Statistics & Machine Learning In R
Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in R
With so many R Statistics & Machine Learning courses around, why enroll for this ?
Regression analysis is one of the central aspects of both statistical and machine learning based analysis. This course will teach you regression analysis for both statistical data analysis and machine learning in R in a practical hands-on manner. It explores the relevant concepts in a practical manner from basic to expert level. This course can help you achieve better grades, give you new analysis tools for your academic career, implement your knowledge in a work setting or make business forecasting related decisions. All of this while exploring the wisdom of an Oxford and Cambridge educated researcher.
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FILE LIST
Filename
Size
1. Get Started with Practical Regression Analysis in R/1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools.mp4
7.8 MB
1. Get Started with Practical Regression Analysis in R/1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools.vtt
1.8 KB
1. Get Started with Practical Regression Analysis in R/2. Data For the Course.html
151 B
1. Get Started with Practical Regression Analysis in R/3. Difference Between Statistical Analysis & Machine Learning.mp4
13.7 MB
1. Get Started with Practical Regression Analysis in R/3. Difference Between Statistical Analysis & Machine Learning.vtt
6.3 KB
1. Get Started with Practical Regression Analysis in R/4. Getting Started with R and R Studio.mp4
18.3 MB
1. Get Started with Practical Regression Analysis in R/4. Getting Started with R and R Studio.vtt
6.6 KB
1. Get Started with Practical Regression Analysis in R/5. Reading in Data with R.mp4
42.6 MB
1. Get Started with Practical Regression Analysis in R/5. Reading in Data with R.vtt
15.2 KB
1. Get Started with Practical Regression Analysis in R/6. Data Cleaning with R.mp4
40.5 MB
1. Get Started with Practical Regression Analysis in R/6. Data Cleaning with R.vtt
16 KB
1. Get Started with Practical Regression Analysis in R/7. Some More Data Cleaning with R.mp4
22.9 MB
1. Get Started with Practical Regression Analysis in R/7. Some More Data Cleaning with R.vtt
8.7 KB
1. Get Started with Practical Regression Analysis in R/8. Basic Exploratory Data Analysis in R.mp4
48.2 MB
1. Get Started with Practical Regression Analysis in R/8. Basic Exploratory Data Analysis in R.vtt
19 KB
1. Get Started with Practical Regression Analysis in R/8.1 EDA.txt.txt
1.1 KB
1. Get Started with Practical Regression Analysis in R/9. Conclusion to Section 1.mp4
4.6 MB
1. Get Started with Practical Regression Analysis in R/9. Conclusion to Section 1.vtt
2.4 KB
1. Get Started with Practical Regression Analysis in R/Regression Analysis_Data and Scripts.zip
934.9 KB
2. Ordinary Least Square Regression Modelling/1. OLS Regression- Theory.mp4
24.9 MB
2. Ordinary Least Square Regression Modelling/1. OLS Regression- Theory.vtt
10.6 KB
2. Ordinary Least Square Regression Modelling/10. Multiple Linear regression with Interaction and Dummy Variables.mp4
37.5 MB
2. Ordinary Least Square Regression Modelling/10. Multiple Linear regression with Interaction and Dummy Variables.vtt
15.9 KB
2. Ordinary Least Square Regression Modelling/11. Some Basic Conditions that OLS Models Have to Fulfill.mp4
30.5 MB
2. Ordinary Least Square Regression Modelling/11. Some Basic Conditions that OLS Models Have to Fulfill.vtt
13.4 KB
2. Ordinary Least Square Regression Modelling/12. Conclusions to Section 2.mp4
7 MB
2. Ordinary Least Square Regression Modelling/12. Conclusions to Section 2.vtt
3.4 KB
2. Ordinary Least Square Regression Modelling/2. OLS-Implementation.mp4
21.6 MB
2. Ordinary Least Square Regression Modelling/2. OLS-Implementation.vtt
9 KB
2. Ordinary Least Square Regression Modelling/3. More on Result Interpretations.mp4
17.1 MB
2. Ordinary Least Square Regression Modelling/3. More on Result Interpretations.vtt
9 KB
2. Ordinary Least Square Regression Modelling/4. Confidence Interval-Theory.mp4
13.7 MB
2. Ordinary Least Square Regression Modelling/4. Confidence Interval-Theory.vtt
6.2 KB
2. Ordinary Least Square Regression Modelling/5. Calculate the Confidence Interval in R.mp4
10.2 MB
2. Ordinary Least Square Regression Modelling/5. Calculate the Confidence Interval in R.vtt
4.9 KB
2. Ordinary Least Square Regression Modelling/6. Confidence Interval and OLS Regressions.mp4
18.6 MB
2. Ordinary Least Square Regression Modelling/6. Confidence Interval and OLS Regressions.vtt
8.1 KB
2. Ordinary Least Square Regression Modelling/7. Linear Regression without Intercept.mp4
8.3 MB
2. Ordinary Least Square Regression Modelling/7. Linear Regression without Intercept.vtt
3.9 KB
2. Ordinary Least Square Regression Modelling/8. Implement ANOVA on OLS Regression.mp4
7.3 MB
2. Ordinary Least Square Regression Modelling/8. Implement ANOVA on OLS Regression.vtt
3.8 KB
2. Ordinary Least Square Regression Modelling/9. Multiple Linear Regression.mp4
14.9 MB
2. Ordinary Least Square Regression Modelling/9. Multiple Linear Regression.vtt
7 KB
3. Deal with Multicollinearity in OLS Regression Models/1. Identify Multicollinearity.mp4
38.2 MB
3. Deal with Multicollinearity in OLS Regression Models/1. Identify Multicollinearity.vtt
16.7 KB
3. Deal with Multicollinearity in OLS Regression Models/1.1 Lecture21_multicol1.txt.txt
1.8 KB
3. Deal with Multicollinearity in OLS Regression Models/2. Doing Regression Analyses with Correlated Predictor Variables.mp4
12.8 MB
3. Deal with Multicollinearity in OLS Regression Models/2. Doing Regression Analyses with Correlated Predictor Variables.vtt
6.6 KB
3. Deal with Multicollinearity in OLS Regression Models/3. Principal Component Regression in R.mp4
25.5 MB
3. Deal with Multicollinearity in OLS Regression Models/3. Principal Component Regression in R.vtt
11.2 KB
3. Deal with Multicollinearity in OLS Regression Models/4. Partial Least Square Regression in R.mp4
17.4 MB
3. Deal with Multicollinearity in OLS Regression Models/4. Partial Least Square Regression in R.vtt
7.8 KB
3. Deal with Multicollinearity in OLS Regression Models/5. Ridge Regression in R.mp4
18.5 MB
3. Deal with Multicollinearity in OLS Regression Models/5. Ridge Regression in R.vtt
7.7 KB
3. Deal with Multicollinearity in OLS Regression Models/6. LASSO Regression.mp4
10.8 MB
3. Deal with Multicollinearity in OLS Regression Models/6. LASSO Regression.vtt
4.5 KB
3. Deal with Multicollinearity in OLS Regression Models/7. Conclusion to Section 3.mp4
5.2 MB
3. Deal with Multicollinearity in OLS Regression Models/7. Conclusion to Section 3.vtt
2.2 KB
4. Variable & Model Selection/1. Why Do Any Kind of Selection.mp4
10.5 MB
4. Variable & Model Selection/1. Why Do Any Kind of Selection.vtt
5.5 KB
4. Variable & Model Selection/2. Select the Most Suitable OLS Regression Model.mp4
33.3 MB
4. Variable & Model Selection/2. Select the Most Suitable OLS Regression Model.vtt
12.6 KB
4. Variable & Model Selection/3. Select Model Subsets.mp4
19.6 MB
4. Variable & Model Selection/3. Select Model Subsets.vtt
9.2 KB
4. Variable & Model Selection/4. Machine Learning Perspective on Evaluate Regression Model Accuracy.mp4
16.9 MB
4. Variable & Model Selection/4. Machine Learning Perspective on Evaluate Regression Model Accuracy.vtt
7.8 KB
4. Variable & Model Selection/5. Evaluate Regression Model Performance.mp4
34.9 MB
4. Variable & Model Selection/5. Evaluate Regression Model Performance.vtt
15.3 KB
4. Variable & Model Selection/6. LASSO Regression for Variable Selection.mp4
8.3 MB
4. Variable & Model Selection/6. LASSO Regression for Variable Selection.vtt
4.1 KB
4. Variable & Model Selection/7. Identify the Contribution of Predictors in Explaining the Variation in Y.mp4
21.9 MB
4. Variable & Model Selection/7. Identify the Contribution of Predictors in Explaining the Variation in Y.vtt
8.6 KB
4. Variable & Model Selection/8. Conclusions to Section 4.mp4
3.9 MB
4. Variable & Model Selection/8. Conclusions to Section 4.vtt
1.8 KB
5. Dealing With Other Violations of the OLS Regression Models/1. Data Transformations.mp4
29 MB
5. Dealing With Other Violations of the OLS Regression Models/1. Data Transformations.vtt
12.4 KB
5. Dealing With Other Violations of the OLS Regression Models/2. Robust Regression-Deal with Outliers.mp4
16.5 MB
5. Dealing With Other Violations of the OLS Regression Models/2. Robust Regression-Deal with Outliers.vtt
7 KB
5. Dealing With Other Violations of the OLS Regression Models/3. Dealing with Heteroscedasticity.mp4
18.3 MB
5. Dealing With Other Violations of the OLS Regression Models/3. Dealing with Heteroscedasticity.vtt
7.1 KB
5. Dealing With Other Violations of the OLS Regression Models/4. Conclusions to Section 5.mp4
2.9 MB
5. Dealing With Other Violations of the OLS Regression Models/4. Conclusions to Section 5.vtt
1.2 KB
6. Generalized Linear Models(GLMs)/1. What are GLMs.mp4
11.8 MB
6. Generalized Linear Models(GLMs)/1. What are GLMs.vtt
5.4 KB
6. Generalized Linear Models(GLMs)/2. Logistic regression.mp4
39.1 MB
6. Generalized Linear Models(GLMs)/2. Logistic regression.vtt
16.1 KB
6. Generalized Linear Models(GLMs)/3. Logistic Regression for Binary Response Variable.mp4
26.4 MB
6. Generalized Linear Models(GLMs)/3. Logistic Regression for Binary Response Variable.vtt
9.5 KB
6. Generalized Linear Models(GLMs)/4. Multinomial Logistic Regression.mp4
15.4 MB
6. Generalized Linear Models(GLMs)/4. Multinomial Logistic Regression.vtt
15.4 MB
6. Generalized Linear Models(GLMs)/5. Regression for Count Data.mp4
14.1 MB
6. Generalized Linear Models(GLMs)/5. Regression for Count Data.vtt
6.2 KB
6. Generalized Linear Models(GLMs)/6. Goodness of fit testing.mp4
8.9 MB
6. Generalized Linear Models(GLMs)/6. Goodness of fit testing.vtt
4.1 KB
6. Generalized Linear Models(GLMs)/7. Conclusions to Section 6.mp4
5.8 MB
6. Generalized Linear Models(GLMs)/7. Conclusions to Section 6.vtt
2.4 KB
7. Working with Non-Parametric and Non-Linear Data/1. Work With Non-Parametric and Non-Linear Data.html
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