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