3 published titles · Same filter in catalogue
Shelf notes for books in this topic.
Reinforcement Learning: An Introduction
This text serves as a thorough reference for reinforcement learning methods and their applications in various fields.
This book explores the application of machine learning techniques in trading environments.
This text serves as a detailed reference on advanced deep learning methods and applications.
Ian Goodfellow et al. · 2016 · MIT Press
Deep Learning provides a comprehensive introduction to the field of deep learning, covering essential mathematical concepts, techniques employed in industry, and research perspectives. It addresses various applications, including natural language processing and computer vision, making it a vital resource for analysts in quantitative finance and technology.
Manish Yarats · David Mann · 2019 · Springer
Machine Learning for Trading provides practitioners with a comprehensive guide to applying machine learning techniques in financial trading. The book covers essential quantitative finance concepts and the integration of technology to enhance trading strategies.
Richard S. Sutton · Andrew G. Barto · 2018 · MIT Press
This comprehensive text on reinforcement learning provides an in-depth exploration of key algorithms and concepts within the field, focusing on both theoretical foundations and practical applications. It covers a range of topics, including online learning algorithms, function approximation, and the intersection of reinforcement learning with psychology and neuroscience.