Automated Machine Learning

This lecture will give an introduction to automated machine learning/deep learning.
It will mainly cover the following topics:

  • Hyperparameter Optimization
  • Bayesian Optimization
  • Neural Architecture Search
  • AutoML in the Age of Foundation Models

Unsupervised Deep Learning

Current issues, methods and datasets of unsupervised learning in image and text processing, including LSTMs, transformers, generative models.

You are going to learn about 

  • Deep understanding of current methods of unsupervised learning of image and text representations, self-supervised learning, representation learning, generative models.
  • Understand, apply and evaluate current approaches.
  • Understanding the technical underpinnings of unsupervised learning methods.
  • Evaluate and discuss new learning problems and unsupervised and self-supervised methods.