The video discusses the intuition for Ordinary Least Squares method and implementation of Linear Regression in Scikit-learn in Python.
Timeline
(Python 3.8)
00:00 - Outline of video
00:46 - What are linear models?
04:06 - What is Ordinary Least Squares?
05:41 - How to calculate parameters?
07:52 - * * * NOTE * * *: the b0, b1 would be same as w0, w1
08:39 - What is Ordinary Least Squares?
10:03 - Ordinary Least Squares: Intuition (linear)
11:53 - Ordinary Least Squares: Intuition (polynomial)
13:03 - What is non-negative least squares?
13:21 - Code snippet
14:10 - Open Jupyter notebook
14:35 - Data
15:03 - Example # 1: LinearRegression(): one feature
19:19 - Method-1: Calculate parameters for linear regression
25:07 - Method-2: Calculate parameters for linear regression
27:15 - Example # 2: LinearRegression(): two features
31:22 - Example # 3: LinearRegression(): positive regression coefficients
34:10 - Ending notes
