Advances in Financial Machine Learning
(Autor) Marcos Lopez de PradoLearn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Marcos Lopez de Prado
Marcos Lopez de Prado is a renowned financial mathematician, author, and professor. He is best known for his groundbreaking work in quantitative finance and machine learning applications in finance. His most notable works include "Advances in Financial Machine Learning" and "Machine Learning for Asset Managers," which have had a significant impact on the field of quantitative finance. Lopez de Prado's writing style is characterized by its clarity, rigor, and practicality, making complex mathematical concepts accessible to a wide audience. His contributions to literature have revolutionized the way financial professionals approach investing and risk management. Lopez de Prado's most famous work, "Advances in Financial Machine Learning," is considered a seminal text in the field and has cemented his reputation as a leading authority in quantitative finance.
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