Master's year 2 · Full module

Advanced Deep Learning with PyTorch

Go further in deep learning with PyTorch: custom training loops, transfer learning, modern architectures and performance tuning.

Learning objectives

• Write a complete PyTorch training loop
• Reuse pretrained models with transfer learning
• Implement advanced architectures
• Optimize training on GPU

Course outline Free preview

1. Tensors, autograd and PyTorch modules
2. Datasets, DataLoaders and training loops
3. Transfer learning
4. Advanced architectures
5. Optimization and scaling
6. Capstone project