We'll learn about gradient descent, a technique for training neural networks. We'll then implement gradient descent from scratch in Python, so you can understand how it works. We'll implement gradient descent by training a linear regression model to predict the weather. In future videos, we'll build on this to create complex neural networks!
You can see a full explanation and code here - https://github.com/VikParuchuri/nnet_course/blob/master/explanations/linreg.ipynb .
Chapters
0:00 Introduction
01:49 - Linear Regression Intuition
07:53 - Measuring Loss
15:28 - Parameter Updates
16:11 - Gradients And Partial Derivatives
23:29 - Learning Rate
28:35 - Implement Linear Regression
36:09 - Training Loop
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