Скачать или смотреть SuperFastCourse: Linear Regression

This course is meant to take you from a college algebra level of understanding to being able to use linear regression for quantitative research, machine learning, and even financial modeling in only 3.5 hours. That's a long time, I wouldn't try to do it in one sitting. But everything is included: what a linear equation means, how coefficients are calculated, the assumptions required to draw statistical inference, etc., and how to do it all in Python!

Chapters:

1. Introduction 00:00
2. Linear Equations 02:48
3. Why Linear Regression? 12:54
4. How to Fit the Model 19:54
5. Ordinary Least Squares 25:25
6. Statistical Inference 32:37
7. Interpreting Results 01:01:25
8. OLS in Python 01:08:26
9. Maximum Likelihood Estimation 01:44:44
10. Gradient Descent 01:55:44
11. Regularization 02:05:08
12. Loss Penalties 02:11:19
13. Regularized Regression in Python 02:27:52
14. Finance Applications 03:01:52
15. Linear Factor Models 03:01:54
16. Important Linear Factor Models 03:04:46
17. Fama-Macbeth Regression in Python 03:09:16
18. Closing Remarks 03:27:20

All notebooks used in this video are available at:
https://github.com/JohnTheQuantYoutub...

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What kinds of videos would you like me to do next?
More machine learning, more programming, or more option pricing/stochastic differential equations? Let me know!