Regularization techniques in Pytorch | Quick Walkthrough | Tutorial for Beginners

Published: 12 January 2024
on channel: Harsh Kumar

391

We look at how to use 5 different regularization techniques in Pytorch. The idea is to provide a practical code walkthrough for the viewer to start working with Pytorch for beginners.

List of regularization techniques discussed in the video are:
1. Batch Normalisation
2. Dropout layer
3. L2 regularisation (weight_decay)
4. Early Stopping
5. Data Augmentation

Notebook on Github: https://github.com/harsh1kumar/learni...

Kaggle Competition/Data Source: https://www.kaggle.com/c/santander-cu...

Credits for Data Augmentation Image: https://www.datacamp.com/tutorial/com...

Timestamp:
00:00 - Intro
00:32 - Get data, preprocess, helper function
02:04 - Batch Normalisation
03:18 - Dropout layer
04:11 - L2 regularisation (weight_decay)
04:34 - Early Stopping
06:36 - Data Augmentation
08:15 - Outro

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