Advanced Econometrics 2: Foundations of Machine Learning

• Tentative Syllabus Syllabus_ML_Oxford_2021.pdf
• Sample exam questions ML_sample_exam.pdf
• Zoom room for lectures Zoom room - Advanced Econometrics, Part I
• Online whiteboard Jamboard - Advanced Econometrics, Part I

Supervised learning: Shrinkage and tuning

• Review of decision theory Slides
• Shrinkage in the normal means model Slides
• Deep neural nets Slides

Active learning: Exploration and exploitation

• Bandit problems Slides
• Reinforcement learning Slides

This course is an abridged version of a longer course on machine learning that I taught before. You can find slides and reading materials for this longer course here: /home/TopicsInEconometrics2019

Reading materials

Papers

• Shrinkage and Gaussian Processes Shrinkage-readings.zip
• Text, forests, neural nets, bandits, reinforcement learning, and visualization DeepNets-Text-Bandits-Visualization-readings.zip

Machine learning books

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

Programming in R

• My introduction to R Slides
• An Introduction to R
• Advanced R
• Hands-On Machine Learning with R
• Bayesian statistics using Stan
  RStan
• Training neural nets using Keras and Tensorflow

Data visualization

• Data Visualization - A Practical Introduction
• An Economist’s Guide to Visualizing Data
• ggplot2 - Elegant Graphics for Data Analysis