# 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

### Active learning: Exploration and exploitation

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