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PyTorch Lightning Tutorial - Lightweight PyTorch Wrapper For ML Researchers
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Classroom Contents
PyTorch Tutorials - Complete Beginner Course
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- 1 PyTorch Tutorial 01 - Installation
- 2 PyTorch Tutorial 02 - Tensor Basics
- 3 PyTorch Tutorial 03 - Gradient Calculation With Autograd
- 4 PyTorch Tutorial 04 - Backpropagation - Theory With Example
- 5 PyTorch Tutorial 05 - Gradient Descent with Autograd and Backpropagation
- 6 PyTorch Tutorial 06 - Training Pipeline: Model, Loss, and Optimizer
- 7 PyTorch Tutorial 07 - Linear Regression
- 8 PyTorch Tutorial 08 - Logistic Regression
- 9 PyTorch Tutorial 09 - Dataset and DataLoader - Batch Training
- 10 PyTorch Tutorial 10 - Dataset Transforms
- 11 PyTorch Tutorial 11 - Softmax and Cross Entropy
- 12 PyTorch Tutorial 12 - Activation Functions
- 13 PyTorch Tutorial 13 - Feed-Forward Neural Network
- 14 PyTorch Tutorial 14 - Convolutional Neural Network (CNN)
- 15 PyTorch Tutorial 15 - Transfer Learning
- 16 PyTorch Tutorial 16 - How To Use The TensorBoard
- 17 PyTorch Tutorial 17 - Saving and Loading Models
- 18 Create & Deploy A Deep Learning App - PyTorch Model Deployment With Flask & Heroku
- 19 PyTorch RNN Tutorial - Name Classification Using A Recurrent Neural Net
- 20 PyTorch Tutorial - RNN & LSTM & GRU - Recurrent Neural Nets
- 21 PyTorch Lightning Tutorial - Lightweight PyTorch Wrapper For ML Researchers
- 22 PyTorch LR Scheduler - Adjust The Learning Rate For Better Results
