Advances in Financial Machine Learning

Brief

Book

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 back test 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.

Artificial Intelligence in Finance: A Python-Based Guide

Brief

Book

This book shows practitioners, students, and academics in both finance and data science how machine and deep learning algorithms can be applied to finance. Thanks to lots of self-contained Python examples, you’ll be able to replicate all results and figures presented in the book.  Examine how data is reshaping finance from a theory-driven to a data-driven discipline  Understand the major possibilities, consequences, and resulting requirements of AI-first finance  Get up to speed on the tools, skills, and major use cases to apply AI in finance yourself  Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets  Delve into the concepts of the technological singularity and the financial singularity