Tutorial 0: Python and PyTorch basics
Environment setup, jupyter, python, tensor basics with PyTorch
Tutorials
All tutorial materials will be available on this page.
The tutorial notebooks can be obtained by cloning the course tutorials repo, or viewed in your browser by using nbviewer.
Tutorial 1: Supervised Learning
Supervised learning framework, binary and multiclass logistic regression, pytorch and autograd basics
Tutorial 2: Multi-layer perceptron
Writing the first deep learning model (Multi layer perceptron), non-linearities etc
Tutorial 3: Convolutional Neural Nets
Convolutional and pooling layers, architectures, spatial classification, residual nets.
Tutorial 4: Optimization
Gradient decent variants
Tutorial 5: Automatic difrentiation
Material
Tutorial 6: Object detection
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Tutorial 7: Recurrent Neural Nets
Material
Tutorial 8: Attention
Material
Tutorial 9: Transformers
Material
Tutorial 10: GAN
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Tutorial 11: VAE
Material
Tutorial 12: Diffusion
Material