Lecture 23 - Learning Rate Decay in Neural Network Optimization

Описание: In this lecture, we learn about learning rate decay and how it can help neural network optimization.

Everything is explained on a whiteboard, and then in Python code.

0:00 Problems with fixed learning rate
3:17 Learning Rate Decay Formula
8:37 Python Code walkthrough
16:56 Visual results through video

Jupyter Notebook access: https://drive.google.com/file/d/1kKVE...

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As we learn AI/ML/DL the material, we will share thoughts on what is actually useful in industry and what has become irrelevant. We will also share a lot of information on which subject contains open areas of research. Interested students can also start their research journey there.

Students who are confused or stuck in their ML journey, maybe courses and offline videos are not inspiring enough. What might inspire you is if you see someone else learning and implementing machine learning from scratch.

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