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