PyTorch-learners-tutorial

• PyTorch tutorial for learners
• Codes are compatible with torch version 1.0.0
• Written in Google Colaboratory (.ipynb files)

PyTorch Basics

1. PyTorch Tensors

• Tensors
• Creating Tensors
• Tensor Data Types
• Size (shape) of Tensors

2. PyTorch datasets - Part 1

• Generating data from NumPy array
• Generating data using custom DataSet and DataLoaders

3. PyTorch datasets - Part 2

• Train-test split
• k-fold Cross-Validation

4. PyTorch Model Basics - nn.Module

• nn.Module
• Data Types
• nn.Sequential

5. PyTorch Model Basics - Building Blocks of Models

• nn.Linear
• Nonlinear Activations
• Loss functions
• Optimizers

6. PyTorch Model Basics - Building Blocks of Models (CNN)

• Convolution & Pooling
• Padding

7. PyTorch Model Basics - Building Blocks of Models (RNN)

• Vanilla RNN
• Gated Recurrent Units
• Long Short Term Memory

Deep Learning with PyTorch

1. Multi Layer Perceptrons - Part 1

• Breast cancer prediction with MLP

2. Multi Layer Perceptrons - Part 2

• CIFAR-10 image classification with MLP

3. Multi Layer Perceptrons - Part 3

• CIFAR-10 image classification with deeper MLP

4. Convolutional Neural Networks - Part 1

• CIFAR-10 image classification with CNN

5. Convolutional Neural Networks - Part 2

• CIFAR-10 image classification with CNN

6. Convolutional Neural Networks - Part 3

• IMDB review sentiment classification with CNN

7. Convolutional Neural Networks - Part 4

• IMDB review sentiment classification with CNN

8. Recurrent Neural Networks - Part 1

-IMDB review sentiment classification with RNN

9. Recurrent Neural Networks - Part 2

• IMDB review sentiment classification with RNN

10. CNN-RNN network

• Fashion MNIST classification with CNN-RNN