Planning and summaries

Files

Class notes are avaliable as a single file here, in pdf format. These notes do not substitute reading the recommended literature.

TIAB_notes.pdf Last updated on 2024-03-18.

Note: these notes will be updated during the semester. It is best not to print them and to check this page regularly for updates.

Slides in html format and can be viewed directly from this page. Use the ← and → keys to change slides or Esc to select specific slides.

Summaries

Note: planned lectures are subject to changes

Lectures 1 and 2, 04-03-2024

Summary

Course overview. Introduction to deep learning.

Lecture 1 (HTML), Lecture 1 (PDF)

Backpropagation. Training artificial neural networks: the computation graph, autodiff, optimization. Introduction to Keras.

Lecture 2 (HTML), Lecture 2 (PDF)

Lectures 3 and 4, 11-03-2024

Summary

Activations and loss functions. Optimizing networks

Lecture 3 (HTML), Lecture 3 (PDF)

Introduction to convolution networks.

Lecture 4 (HTML), Lecture 4 (PDF)

Lectures 5 and 6, 18-03-2024

Summary

Unsupervised learning with ANN. Autoencoders and Convolutional Autoencoders.

Lecture 5 (HTML), Lecture 5 (PDF)

Representation learning and feature extraction.

Lecture 6 (HTML), Lecture 6 (PDF)

Lectures 7 and 8, 25-03-2024

Summary

Introduction to Ontologies and Bio-ontologies,

Lecture 7 (HTML), Lecture 7 (PDF)

OWL Language

Lecture 8 (HTML), Lecture 8 (PDF)

Lectures 9 and 10, 08-04-2024

Summary

OBO language, Gene Ontology

Lecture 9 (HTML), Lecture 9 (PDF)

Usage of the Gene Ontology

Lecture 10 (HTML), Lecture 10 (PDF)

Lectures 11 and 12, 15-04-2024

Summary

Natural Language Processing, Language Models

Lecture 11 (PDF)

Biomedical text mining

Lecture 12 (PDF)