Course: Learn PyTorch
- 1 Introduction to PyTorch and Tensors
- 2 Autograd: Automatic Differentiation
- 3 Building Neural Networks with torch.nn
- 4 Data Handling and Preprocessing
- 5 Training a Model: The Optimization Loop
- 6 Saving, Loading, and Checkpointing Models
- 7 Convolutional Neural Networks (CNNs) for Vision
- 8 Recurrent Neural Networks (RNNs) for Sequence Data
- 9 Transformers and Attention Mechanisms
- 10 Advanced Optimization and Hyperparameter Tuning
- 11 Distributed Training and Scaling
- 12 Model Deployment and Production