Technical Ebook

Using Causal Inference

to Unpack the Why and What If

In an MIT article, computer science researcher Jeannette Wing says that “Causality … is the next frontier of AI and machine learning.” This technical ebook unpacks a hearty introduction to causal inference and all its idiosyncrasies, as well as the danger of using regular ML to infer causal effects.
Causal Inference - 3D-Cover-Mockup

Get the Technical Ebook

How Does Causal ML Differ From Traditional ML?

This Technical Ebook Highlights:

  • The foundational distinction between correlation and causation
  • A common application of causal inference, uplift modeling, in the lens of churn prediction
  • Three key aspects that highlight how traditional and causal ML differ along with the main assumptions made on data for causal ML (i.e., conditional ignorability, common support, and no interference)

Copyright © 2022 Dataiku. All rights reserved. | Online Privacy