In yesterday's live stream—*Live 68*—we took a look at the linear regression following Aurélien Géron's *Hands-On Machine Learning* book. We saw the *normal equation*, how to calculate the dot product of two matrices and the inverse of a matrix, and saw a few different ways in which, with code, you can solve a linear equation, plus how to do it with Sci-Kit Learn's `LinearRegression`

class.

You can take a look at the Linear Regression Colab notebook.

Use the timestamps below to jump to specific parts of the stream.

If this is something that interests you, please let me know on Twitter or, even better, on the Discord community.

*Thanks for watching.*

*See you next week!*

- 2:05 Introduction
- 4:57 Blog
- 5:42 Thoughts on streaming and podcasting
- 9:40 Digital art experiments with p5.js
- 15:31 Plotting a linear equation
- 22:30 Linear regression and matrices
- 33:13 DALL·E 2
- 41:25 Matrix dot product
- 48:40 Inverse of a matrix
- 53:48 The normal equation
- 1:00:24 Linear regression with Sci-Kit Learn