Pytorch-Tutorial

Here is the tutorial series I prepared during the intelligent systems course.

Topics

We will disscuss the following topics in order:

1. Pytorch Basics
2. Gradient and Backpropagation
3. Creating a Neural Net class using Inheritance of nn.Module
4. Dataset and Data Loader attributes and examples
5. How to implement CrossEntropyLoss(CEE) & BinaryCrossEntropyLoss(BCE) ?
6. Different ways to define Activation functions using torch, torch.nn, torch.nn.functional
7. A thorough example of implementing a Feedforward neural net using the MNIST dataset
8. Transfer Learning (Fine-tuning & Freezing), saving the model's best performance

Lectures

• Part1: https://youtu.be/8g_Wy6_Pv4o
• Part2: https://youtu.be/9s4mlX-fauU
• Part3: https://youtu.be/0tYNfyobT24
• Part4: https://youtu.be/0q1rTbNShic