(videolecture04)=

# Videolecture 4. Linear Classification and Regression

1\. Logistic regression: theory, from Machine Learning perspective

<p align="center"><iframe width="560" height="315" style='' src="https://www.youtube.com/embed/l3jiw-N544s" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></p>

2\. Logistic regression: practice. Beating baselines in the "Alice" [competition](https://inclass.kaggle.com/c/catch-me-if-you-can-intruder-detection-through-webpage-session-tracking2).

<p align="center"><iframe width="560" height="315" style='' src="https://www.youtube.com/embed/7o0SWgY89i8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></p>

3\. Ordinary Least Squares, LASSO, and Ridge: theory.

<p align="center"><iframe width="560" height="315" style='' src="https://www.youtube.com/embed/ne-MfRfYs_c" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></p>

4\. A business case with a regression task – predicting customer Life-Time Value.

<p align="center"><iframe width="560" height="315" style='' src="https://www.youtube.com/embed/B8yIaIEMyIc" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></p>