Module 06
Deep Learning
Where your signals-and-systems instincts pay off. Build the intuition and the training craft, not just the API calls.
21 topics ~117 h estimated learning time
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- 6.1 From perceptron to multilayer network
Foundation · 5 h
- 6.2 Backpropagation by hand
Core · 6 h
- 6.3 Activations and initialization
Core · 5 h
- 6.4 Loss functions
Core · 4 h
- 6.5 Optimizers and learning-rate schedules
Core · 5 h
- 6.6 Regularization and augmentation
Core · 5 h
- 6.7 Normalization layers
Core · 4 h
- 6.8 PyTorch: tensors, autograd, modules
Core · 8 h
- 6.9 The training loop, datasets, dataloaders
Core · 6 h
- 6.10 Debugging deep learning
Core · 5 h
- 6.11 Image processing fundamentals for machine learning
Core · 4 h
- 6.12 Convolutional networks
Core · 7 h
- 6.13 Modern vision architectures
Advanced · 6 h
- 6.14 Transfer learning and fine-tuning
Core · 5 h
- 6.15 Object detection and segmentation
Advanced · 6 h
- 6.16 Recurrent networks and their limits
Core · 6 h
- 6.17 Attention from first principles
Core · 6 h
- 6.18 Autoencoders and representation learning
Core · 5 h
- 6.19 Generative models: GANs and diffusion
Advanced · 8 h
- 6.20 Self-supervised and contrastive learning
Advanced · 5 h
- 6.21 Scaling training: precision, accumulation, distribution
Advanced · 6 h