Python for Simple, Multiple and Polynomial Regression Models

سرفصل های دوره

Complete Linear Regression Analysis - Theory, Intuition, Mathematics and Implementation in Python.

1. Introduction

1. Introduction of the Course

2. Course Outline

3.1 Course Material.zip

3. Course Material.html

2. Python Crash Course

1. Introduction of the Section

2. Installing Python Package

3. Introduction of Jupyter Notebook

4. Arithmetic With Python Part-01

5. Arithmetic With Python Part-02

6. Arithmetic With Python Part-03

7. Dealing With Arrays Part-01

8. Dealing With Arrays Part-02

9. Dealing With Arrays Part-03

10. Plotting and Visualization Part-01

11. Plotting and Visualization Part-02

12. Plotting and Visualization Part-03

13. Plotting and Visualization Part-04

14. Lists In Python

15. for loops Part-01

16. for loops Part-02

3. Regression Analysis by Least Square Method

1. Slope-Intercept Form

2. Definition of Regression

3. Multiple Regression

4. Least Square Regression Part-01

5. Least Square Regression Part-02

6. Least Square Regression Part-03

7. Simple Regression in Python Part-01

8. Simple Regression in Python Part-02

9. Multiple Regression in Python Part-01

10. Multiple Regression in Python Part-02

11. Multiple Regression in Python Part-03

12. Polynomial Regression

13. Polynomial Regression in Python

14. Summary of Polynomial Regression

4. Regression By Gradient Descent

1. Introduction of Gradient Descent

2.1 4.2-Pictorial Explanation of Gradient descent

2. Pictorial Explanation of Gradient Descent

3. Gradient Descent and Least Square Regression

4. Gradient Descent in Python Part-01

5. Gradient Descent in Python Part-02

5. Overfitting and Regularization

1. Introduction to Overfitting and Regularization

2. Ridge Regression

3. Ridge Regression in Python

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تولید کننده: Udemy