I teach the following courses at MIT:
Occasionally, I write brief notes to supplement the lecture materials. Those notes, as well as my Medium posts on data science, are gathered here.
I hope you find the notes useful. Feedback is welcome (@rama100, )
Exploring Data and Drawing Conclusions
Advice from the Data Science “Trenches”
The Intuition Behind Models and Algorithms
From Prediction to Action — How to Learn Optimal Policies From Data
If you know how to build predictive models, you can leverage this knowledge to learn optimal policies - rules that tell you the best way to act in various situations - directly from data.
Policy optimization problems are very common in the business world (e.g., arguably, every personalization problem is a policy optimization problem) and knowing how to solve them is a data science superpower. The following series of blog posts aims to give you that superpower :-)
- In Part 1, I motivate the need to learn optimal policies from data. Policy optimization covers a vast range of practical situations and I briefly describe examples from healthcare, churn prevention, target marketing and city government.
- In Part 2, I walk through how to create a dataset so that it is suited for policy optimization.
- In Part 3, I describe a simple (and, in my opinion, magical) way to use such a dataset to estimate the effectiveness of any policy..
- In Part 4, I show how to use such a dataset to find an optimal policy.
Getting Your Hands on Useful Datasets