Overview

This book is an introductory guide for data scientists to learn the mathematical principles behind the most well-known AI algorithms. The author proposes two original theoretical concepts: the accordion theory and the recurrent third iteration theory. He then applies them to real cases. This work covers topics of higher mathematics from algebraic topology and spectral theory to functional analysis and ergodic theory. These concepts are fundamental to understanding AI concepts and algorithms. This deepens both practitioners' and managers' knowledge of mathematical modeling and assists them to engage with specialized literature. More importantly this book will help them to formally write their own ideas and research.

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9781739203177

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Serge Plata received his PhD in mathematics from Imperial College London. He also received an EMBA at Harvard Business School and was awarded a fellowship at the Institute of Mathematics and its Applications in the UK. He is a chartered mathematician (Royal Charter) and a chartered scientist (UK Science Council) in the UK. He is author of Visions of Applied Mathematics (Peter Lang, 2007) and other papers, articles and editorials for specialized magazines. He has been the keynote speaker at several data events and academic conferences in the UK and abroad. He is a certified six-sigma black belt. He has held directorship and leadership roles in data science, AI, analytics and R&D for FTSE100 and S&P 500 companies, start-ups and international management and technology consultancies.

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