Learn PyTorch
Curriculum
12 Topics- 01 Introduction to PyTorch and Tensors
- 02 Autograd: Automatic Differentiation
- 03 Building Neural Networks with torch.nn
- 04 Data Handling and Preprocessing
- 05 Training a Model: The Optimization Loop
- 06 Saving, Loading, and Checkpointing Models
- 07 Convolutional Neural Networks (CNNs) for Vision
- 08 Recurrent Neural Networks (RNNs) for Sequence Data
- 09 Transformers and Attention Mechanisms
- 10 Advanced Optimization and Hyperparameter Tuning
- 11 Distributed Training and Scaling
- 12 Model Deployment and Production