/PyTorch-learners-tutorial

PyTorch tutorial for learners

Primary LanguageJupyter Notebook

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