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 0: Python and PyTorch basics

1 minute read

Environment setup, jupyter, python, tensor basics with PyTorch

1 minute read

Supervised learning framework, binary and multiclass logistic regression, pytorch and autograd basics

less than 1 minute read

MLP model, activations, backprop, loss functions and optimization in PyTorch

less than 1 minute read

Convolutional and pooling layers, architectures, spatial classification, residual nets.

less than 1 minute read

From resnet to mobilenet, guild to efficient CNNs

less than 1 minute read

Descent-based methods, backpropagation, automatic differentiation, bi-level optimization, time-series analysis with CNNs.

less than 1 minute read

Evaluation methods (mAP, mIoU), two stage models (RCNN), one stage models (yolo)

less than 1 minute read

Transfer learning definition and contexts, fine-tuning pre-trained models, unsupervised domain adaptation via an adversarial approach.

less than 1 minute read

RNN, BPTT and TBTT, LSTM and GRU, sentiment analisys and stock prediction.

less than 1 minute read

The attention mechanisem. soft and hard, multiplicative and additive, scaled dot product, attention for alignment translation

less than 1 minute read

Transformers :)

less than 1 minute read

Generative vs Discriminative models VAE

less than 1 minute read

GAN, WGAN, conditional GAN, styleGAN and more