Yes! Six Causality Books That Will Get You From Zero to Advanced (2023)

…and you can get 3 of them completely for free if you want! 🤗

Aleksander Molak
9 min readOct 17, 2022

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The six causal books. Image by yours truly.

Introduction

Recent years brought a sharp increase in interest in causal methods in the research community and in the industry. One of the challenges that people entering the field face is a lack of standardized resources and terminology. Causality research has been scattered and divided into sub-fields for decades. One of the consequences of this fact is that many newcomers feel overwhelmed and confused when they enter the field.

I was in the same spot a couple years ago.

In this post I want to share with you six causal books that allowed me to structure and speed-up my causal journey. I hope they will help you achieve the same!

And yes, you got it right, you can get 3 of these books for free, 100% legally if you choose so! 😯

For every book I’ll provide you with 5 bullet points highlighting the most important topics covered in the book. I’ll also provide you with links to get a copy and/or a free copy of a book if it’s available.

If you’re a Python person interested in causality, sign up for my email list here: https://causalpython.io to get free exclusive content and updates on my upcoming causal inference & discovery book right in your inbox!

Let’s start!

1. Starting Strong: “The Book of Why

Figure 1. “The Book of Why” by Judea Pearl and Dana Mackenzie. Image by yours truly.
Figure 1. “The Book of Why” by Judea Pearl and Dana Mackenzie. Image by yours truly.

“The Book of Why” by the godfather of modern causality Judea Pearl and his co-author, former mathematician Dana Mackenzie is a starting point for many and not by accident.

You can think of it as a comprehensive introduction to the field. It’s a mixture of theory, history, storytelling, math and practical exercises. If that sounds like a lot, don’t worry, it’s really well-structured and fun to read! The authors cover the history of causality, the basic theory behind Pearl’s do-calculus and share inspiring examples of the applications of causal inference in the…

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Aleksander Molak

Consultant, Researcher, Educator, Author || Causality, NLP & Probabilistic Modeling || Learn more: bit.ly/learn-more-medium