Machine Learning for Public Policy

The current version of this course is being offered in Spring 2019 at the University of Chicago.

Rayid Ghani

Textbooks:

There is no book that covers this topic well. We will use two textbooks as recommended and augment through class lectures:

1. Data Science for Business. Foster Provost and Tom Fawcett
2. Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Peter Flach

This is the repository for the Machine Learning for Public Policy class at the University of Chicago. It contains:

• Lectures
• Assignments
• Lab Notebooks
• Readings
• Project Guidelines
• Practical Tools and Tips

You can also take a look at the Syllabus as well as the weekly schedule.

Schedule

Some useful resources for background and labs

• Unix Command line tutorial
• Git and Github
• Getting data from text files into a database
• Sample notebook for machine learning