After a slow start, the finance industry is quickly catching up with others in its adoption of AI. Joe Rothermich explains how Thomson Reuters Labs is using AI to perform research in building quantitative investment models and discusses the company's research in deep learning for credit risk, machine learning and NLP for unlocking alternative datasets, and financial graph-based analytics.
Table of contents
- Title: How Thomson Reuters is using AI in quantitative finance applications
- Release date: July 2019
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920422396
You might also like
40 Algorithms Every Programmer Should Know
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …
Software Engineering at Google
Today, software engineers need to know not only how to program effectively but also how to …
Designing Data-Intensive Applications
Data is at the center of many challenges in system design today. Difficult issues need to …
Advances in Financial Machine Learning
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks …