dmachlanski / iads-summer-school-causality-2021

A one-day workshop on causal inference from observational data provided as part of IADS Summer School in July 2021.

Machine Learning for Causal Inference from Observational Data (29 July 2021)

Agenda

• Welcome and Introduction to the Course
• Causal Inference using Machine Learning
• Short Break
• Practical Part 1: Guided Example
• Lunch Break
• Practical Part 2: Do It Yourself
• Consolidation, Discussion and Next Steps

Signing-up for Google Colab

1. Create a Google account if you do not have one already.
2. Go to https://colab.research.google.com/.
3. If you see a “Sign in” button in the top right corner of the screen, click it and sign in using your Google account. If you see your account’s profile picture instead, you are already signed in.
4. In the top right corner of the screen, there is also a “Connect” button. Click it. A successful connection will confirm you are logged in correctly.
5. Feel free to explore the default “Welcome to Colaboratory” notebook (the one opened by default when you visit the website). Execute some code cells and familiarise yourself with the environment. This step is entirely optional as we will cover this in the course.

Further resources

• Introduction to Causal Inference online course.
• Recent causal inference surveys:
  • https://doi.org/10.1145/3397269
  • http://arxiv.org/abs/2002.02770
• EconML.
• Python courses.
• Scikit-learn docs.
• Scientific Python ecosystem - SciPy.