From the back cover:
Causal AI teaches you how to build machine learning and deep learning models that implement causal reasoning. Discover why leading AI engineers are so excited by causal reasoning, and develop a high-level understanding of this next major trend in AI. New techniques are demonstrated with example models for solving industry-relevant problems. You'll learn about causality for recommendations; causal modeling of online conversions; and uplift, attribution, and churn modeling. Each technique is tested against a common set of problems, data, and Python libraries, so you can compare and contrast which will work best for you.
About the reader:
For data scientists and machine learning engineers. A familiarity with probability and statistics will be helpful, but not essential, to begin this guide. Examples in Python.
