This repository contains
- Course notes
- Assignments
- Additional resources (collected for better understanding of the concepts)
- Course author(s): AI Summer
- Course Website
- Chapter 0: Learn Deep Learning
- Chapter 1: Neural Networks
- Chapter 2: Training Neural Networks
- Chapter 3: Convolutional Neural Networks
- Chapter 4: Recurrent Neural Networks
- Chapter 5: Autoencoders
- Chapter 6: Generative Adversarial Networks
- Chapter 7: Attention and Transformers
- Chapter 8: Graph Neural Networks
- Conclusion
| Chapter | Assignment | Description |
|---|---|---|
| #1 | Train linear classifier | Train a linear classifier with dummy input values. |
| #2 | Train a Neural Network | Train a neural network to classify CIFAR10 images into one of the 10 classes. |
| #3 | Build and Train CNN | Build and train CNN on CIFAR dataset. This assignment is a follow-up of previous assignment (Chapter #2). Here feedforward network is replaced by CNN. |
| #3 | Batch Normalization | Batch normalization function |
| #3 | Skip Connection | ResNet skip connection class |
| #4 | LSTM cell | Develop an LSTM cell from scratch. |
| #4 | RNN | RNN |
| #5 | Autoencoder | Filter size computed from the equation for number of parameters. |
| #5 | ELBO | Evidence lower bound (ELBO) |
| #5 | Reparameterization trick | Reparameterization trick |
| #6 | GAN | Generative Adversarial Network |
| #7 | Transformer Encoder | A simple transformer encoder |
| #8 | Graph Laplacian | Graph Laplacian |
| #8 | Spectral Image Segmentation | Spectral Image Segmentation with Graph Laplacian |
| #8 | Chebyshev approximation | Chebyshev approximation for the Laplacian powers |
| #8 | GCN | 1-hop Graph Convolutional Network |
- Course completion certificate
- Issued on August 2023
-
Deep Learning PyTorch Fundamentals
- Explains the basics of PyTorch model training using a simple regression and a classification problem.
- The steps involved in the training process are better explained in this course.
-
Natural Language Processing with Deep Learning (CS224n)
- Stanford University course by Prof. Christopher Manning
- The repository contains my assignment solutions.
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