Machine Learning, Statistics, Mathematics eBooks and Articles
Home | About the Author | Newsletter | Our Catalog | Free Books | Contact UsUpdate: My new book Off the Beaten Path Tutorial: Stochastic Processes is now published. You can access it here. To receive updates about new and upcoming books, Sign up here on our sister website MLTechniques.com.
Welcome to our digital library! You will find here eBooks, articles and tutorials covering original, off-the-beaten-path content in machine learning, operations research, statistics, dynamical systems, mathematics and related topics. Written by Vincent Granville PhD, the emphasis is on applications, the style is compact, and many illustrations are provided, including source code and Excel spreadsheets. Concepts are explained in simple English, avoiding jargon and arcane theories. Yet new, unpublished research-level material is presented to the readers interested in digging deeper.
Basins of attraction of the sine map, with smooth and chaotic areas
Our digital catalog
The prerequisite to read my books or articles is typically one year of calculus and/or probability at the undergraduate level. I focus on simple techniques, easy to understand and implement, yet very efficient with broad applications: for instance, model-free regression techniques or confidence intervals. It will appeal to engineers, physicists, mathematicians, MBA professionals, quants, software engineers and scientists interested in expanding their analytical horizons. Many original exercises included in most articles and eBooks are of interest both to college students and professors in Academia, offering a fresh and exciting perspective on the topics being discussed.Upcoming Textbooks and Articles
- Simulation: standard and non-standard probability distribution, cluster processes
- Original maths, stats and probability exercises
- Random number generation, encryption, and secure passwords
- Simple, overlooked, yet efficient statistical techniques
- Original introduction to discrete dynamical systems
- A catalog of beautiful mathematical images
- New perspectives on some famous mathematical conjectures
- Experimental machine learning on synthetic data
- The probabilistic method in number theory
- Off-the-beaten-path introduction to linear algebra
- Time series modeling: best kep secrets
- A plethora of unusual, little known probability distributions
- Recreational Mathematics
- Free online platforms for mathematicians
About the Author
Vincent Granville, PhD is a pioneering data scientist, mathematician, entrepreneur, investor, co-founder of Data Science Central (acquired in 2020), former VC-funded executive, author and patent owner. Vincent's past corporate experience includes Visa, Wells Fargo, eBay, NBC, Microsoft, CNET, InfoSpace and other Internet startup companies (one acquired by Google). Vincent is also a former post-doct from Cambridge University, and the National Institute of Statistical Sciences (NISS).
Vincent published in Journal of Number Theory, Journal of the Royal Statistical Society (Series B) and IEEE Transactions on Pattern Analysis and Machine Intelligence. One of his books was published by Wiley. For details, see my Google Scholar profile, here.