Advances in Financial Machine Learning

Nonfiction, Computers, Advanced Computing, Theory, Business & Finance, Finance & Investing, Investments & Securities
Cover of the book Advances in Financial Machine Learning by Marcos Lopez de Prado, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Marcos Lopez de Prado ISBN: 9781119482109
Publisher: Wiley Publication: February 2, 2018
Imprint: Wiley Language: English
Author: Marcos Lopez de Prado
ISBN: 9781119482109
Publisher: Wiley
Publication: February 2, 2018
Imprint: Wiley
Language: English

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular 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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular 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.

More books from Wiley

Cover of the book Qualitative Research in Nursing and Healthcare by Marcos Lopez de Prado
Cover of the book A Companion to Ethnicity in the Ancient Mediterranean by Marcos Lopez de Prado
Cover of the book Shadow Banking in China by Marcos Lopez de Prado
Cover of the book Extended Finite Element Method for Crack Propagation by Marcos Lopez de Prado
Cover of the book Working With Families: Guidelines and Techniques by Marcos Lopez de Prado
Cover of the book Chemistry and Technology of Emulsion Polymerisation by Marcos Lopez de Prado
Cover of the book Geochemical Sediments and Landscapes by Marcos Lopez de Prado
Cover of the book Ambition: Why It's Good to Want More and How to Get It by Marcos Lopez de Prado
Cover of the book ANOVA and ANCOVA by Marcos Lopez de Prado
Cover of the book Sensory Discrimination Tests and Measurements by Marcos Lopez de Prado
Cover of the book Lead, Sell, or Get Out of the Way by Marcos Lopez de Prado
Cover of the book Unleashing Excellence by Marcos Lopez de Prado
Cover of the book Integrating Biological Control into Conservation Practice by Marcos Lopez de Prado
Cover of the book Public Participation for 21st Century Democracy by Marcos Lopez de Prado
Cover of the book The One-Hour Activist by Marcos Lopez de Prado
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy