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This book is organized by [TheQuantHackers Community] (https://llmquant.com/) and provides PDF downloads. It is only for learning and communication. The copyright belongs to the original author.
This book is organized by [TheQuantHackers Community] () and provides PDF downloads. It is only for learning and communication. The copyright belongs to the original author.
"Artificial Intelligence in Finance: A Python-Based Guide" is a practical financial professional book that provides an in-depth exploration of how to use artificial intelligence and machine learning techniques to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. This book introduces in detail the application of machine learning and deep learning algorithms in the financial field, including core mathematical technologies such as neural networks and reinforcement learning. Through a large number of Python examples, the book helps readers understand how data is reshaping the financial industry and master the tools, skills and main use cases for applying AI to finance. The content covers everything from the basic concepts of AI to how to identify and exploit economic inefficiencies through backtesting and automated trading strategies. It aims to enhance readers' professional capabilities in the field of quantitative finance. Whether they are financial practitioners, students or academic researchers, they can gain valuable knowledge and practical experience.
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本书籍由TheQuantHackers社区整理, 并提供PDF下载, 只供学习交流使用, 版权归原作者所有。
作者: Yves J. Hilpisch
出版社: O'Reilly Media
出版年份: 2020
难度: ⭐⭐⭐⭐
推荐指数: ⭐⭐⭐⭐⭐
PDF下载: 点击下载
《Artificial Intelligence in Finance: A Python-Based Guide》是一本实用的金融专业书籍，深入探讨了如何利用人工智能和机器学习技术来发现金融市场中的统计低效性，并通过算法交易进行利用。本书详细介绍了机器学习和深度学习算法在金融领域的应用，包括神经网络和强化学习等核心数学技术。书中通过大量的Python示例，帮助读者理解数据如何重塑金融行业，并掌握将AI应用于金融的工具、技能和主要用例。内容涵盖了从AI的基本概念到如何通过回测和自动化交易策略来识别和利用经济低效性，旨在提升读者在量化金融领域的专业能力，无论是金融从业者、学生还是学术研究者，都能从中获得宝贵的知识和实践经验。
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