Foundations of Machine Learning - Oxford summerschool 2024

Tentative Syllabus: Syllabus_ML_Oxford_summerschool_2024.pdf

Summer school homepage: september-summer-school

Lecture slides

1. Supervised learning using Python Jupyter Notebook, Html version
   Probably approximately correct learning theory Slides
2. Shrinkage in the normal means model Slides
3. Deep neural nets Slides
   Transformer models for natural language processing Slides
4. Overview of online learning and active learning Slides
   Online learning Slides
   Bandit problems Slides
5. Fairness Slides
   Differential privacy Slides

Problems for the practice sessions

1. Coding exercise - supervised learning: coding_exercise_supervised.pdf
2. Coding exercise - shrinkage estimation: coding_exercise_shrinkage.pdf
3. Coding exercise - multiarmed bandits: coding_exercise_bandits.pdf

Useful links

Machine learning books

• The Elements of Statistical Learning
• Understanding machine learning: From theory to algorithms
• Gaussian Processes for Machine Learning
• Deep Learning
• Speech and Language Processing
• Reinforcement learning - An introduction
• The Ethical Algorithm

Programming in Python

• A Whirlwind Tour of Python
• Python Data Science Handbook

Programming in R

• An Introduction to R
• R for Data Science
• Advanced R
• Hands-On Machine Learning with R

Data visualization

• Data Visualization - A Practical Introduction
• An Economist’s Guide to Visualizing Data