PyTorch Lightning TutorialsΒΆ
- Tutorial 1: Introduction to PyTorch
- Tutorial 2: Activation Functions
- Tutorial 3: Initialization and Optimization
- Tutorial 4: Inception, ResNet and DenseNet
- Tutorial 5: Transformers and Multi-Head Attention
- Tutorial 6: Basics of Graph Neural Networks
- Tutorial 7: Deep Energy-Based Generative Models
- Tutorial 8: Deep Autoencoders
- Tutorial 9: Normalizing Flows for Image Modeling
- Tutorial 10: Autoregressive Image Modeling
- Tutorial 11: Vision Transformers
- Tutorial 12: Meta-Learning - Learning to Learn
- Tutorial 13: Self-Supervised Contrastive Learning with SimCLR
- GPU and batched data augmentation with Kornia and PyTorch-Lightning
- Barlow Twins Tutorial
- PyTorch Lightning Basic GAN Tutorial
- PyTorch Lightning CIFAR10 ~94% Baseline Tutorial
- PyTorch Lightning DataModules
- Fine-Tuning Scheduler
- Introduction to PyTorch Lightning
- TPU training with PyTorch Lightning
- How to train a Deep Q Network
- Finetune Transformers Models with PyTorch Lightning