«'Agostino Capponi and Charles-Albert Lehalle have edited an excellent book that addresses important questions regarding the application of machine learning and data science techniques to the challenging field of finance. I highly recommend this book to readers interested in our field.' Marcos López de Prado, Abu Dhabi Investment Authority & Cornell University»

«'Beginning with the 1973 publication of the Black–Scholes formula, mathematical models coupled with computing revolutionized finance. We are now witnessing a second revolution as larger-scale computing makes data science and machine learning methods feasible. This book demonstrates that the second revolution is not a departure from, but rather a continuation of, the first revolution. It will be essential reading for researchers in quantitative finance, whether they were participants in the first revolution or are only now joining the fray.' Steven E. Shreve, Carnegie Mellon University»

«'Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices' comes at a critical time in the financial markets. The amount of machine readable data available to practitioners, the power of the statistical models they can build, and the computational power available to train them keeps growing exponentially. AI and machine learning are increasingly embedded into every aspect of the investing process. The common curriculum, however, both in finance and in applications of machine learning, lags behind. This book provides an excellent and very thorough overview of the state of the art in the field, with contributions by key researchers and practitioners. The monumental work done by the editors and reviewers shows in the wide diversity of current topics covered – from deep learning for solving partial differential equations to transformative breakthroughs in NLP. This book, which I cannot recommend highly enough, will be useful to any practitioner or student who wishes to familiarize themselves with the current state of the art and build their careers and research on a solid foundation.' Gary Kazantsev, Bloomberg and Columbia University»