GenAI and Machine Learning Books

eBooks covering generative AI, machine learning optimization, data science, explainable AI, experimental math, chaotic dynamical systems and stochastic processes, synthetic data, statistical engineering, predictive modeling, business analytics, and advanced simulations. You will learn how to build faster, better applications that are easy to implement, requiring less data yet outperforming vendor solutions according to sound evaluation metrics. 

For business professionals, software engineers, developers, scientists, researchers, consultants, analytic practitioners, and anyone dealing with challenging data and AI problems. Featuring state-of-the-art techniques, geared towards applications, explained in simple English.

Our books are in PDF format. Authored by Vincent Granville and easy to navigate, they are illustrated with efficient algorithms, numerous figures, videos, case studies, best practices, and enterprise-grade projects with solutions. Source code (Python) and data sets are available on GitHub. 

For details about any specific book, click on the related picture.