Before Machine Learning Volume 3 - Probability and Statistics for A.I: The fundamental mathematics for Data Science

What happens when the world’s greatest diamond heist meets the world of probability and statistics? In this captivating and conversational guide, the 2003 Antwerp Diamond Heist serves as a rich backdrop to explain the core concepts of probability and statistics for artificial intelligence. Through the lens of the heist, we’ll explore the deeper workings of Bayesian statistics, Markov Chains, and other powerful techniques, all while uncovering how these ideas apply to modern AI.

Though the storytelling makes the content light and engaging, the book never loses sight of the mathematical rigor needed to master these topics.

In this book, you’ll discover:

Intriguing Heist Narratives: Learn key concepts such as hypothesis testing, confidence intervals, and Bayesian reasoning, all embedded in the narrative of one of history's most notorious heists.
Advanced AI Techniques: Dive into Monte Carlo methods, Markov Chains, Gibbs sampling, the Metropolis-Hastings algorithm, and hierarchical Bayesian models—all tied back to the clever strategies of the heist.
Hands-On Learning: Understand the real-world application of statistical methods with accompanying code, designed to solidify each concept through practical exploration.


Join the journey where a diamond heist helps you crack the code of probability and statistics in AI.