Description: Reinforcement Learning for Finance : A Python-based Introduction, Paperback by Hilpisch, Yves J., ISBN 109816914X, ISBN-13 9781098169145, Brand New, Free shipping in the US Reinforcement learning (RL) has led to several breakthroughs in AI. The use of the Q-learning (DQL) algorithm alone has helped people develop agents that play arcade games and board games at a superhuman level. More recently, RL, DQL, and similar methods have gained popularity in publications related to financial research. This book is among the first to explore the use of reinforcement learning methods in finance. Author Yves Hilpisch, founder and CEO of The Python Quants, provides the background you need in concise fashion. ML practitioners, financial traders, portfolio managers, strategists, and analysts will focus on the implementation of these algorithms in the form of self-contained Python code and the application to important financial problems. This book covers:Reinforcement learningDeep Q-learningPython implementations of these algorithmsHow to apply the algorithms to financial problems such as algorithmic trading, dynamic hedging, and dynamic asset allocation This book is the ideal reference on this topic. You'll read it once, change the examples according to your needs or ideas, and refer to it whenever you work with RL for finance. Dr. Yves Hilpisch is founder and CEO of The Python Quants, a group that focuses on the use of open source technologies for financial data science, AI, asset management, algorithmic trading, and computational finance.
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End Time: 2024-11-26T05:22:00.000Z
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Book Title: Reinforcement Learning for Finance : A Python-based Introduction
Number of Pages: 212 Pages
Publication Name: Reinforcement Learning for Finance : a Python-Based Introduction
Language: English
Publisher: O'reilly Media, Incorporated
Subject: Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Publication Year: 2024
Item Height: 0.6 in
Item Weight: 23.5 Oz
Type: Textbook
Author: Yves J. Hilpisch
Subject Area: Computers
Item Length: 9.8 in
Item Width: 5.9 in
Format: Trade Paperback
