《Progress in Financial Machine Learning》一书聚焦于金融领域机器学习技术的应用与进展，探讨了算法交易、风险管理和量化投资策略等前沿话题。
Machine learning (ML) is revolutionizing nearly every aspect of our lives. Today, ML algorithms can accomplish tasks that only expert humans could perform until recently. In the realm of finance, this marks an incredibly exciting period for adopting disruptive technologies that will redefine how everyone invests for generations to come.
Readers will learn how to structure big data in a way that is suitable for ML algorithms; conduct research using these algorithms on such datasets; leverage supercomputing methods; and backtest their findings while minimizing false positives. The book addresses real-life challenges faced by practitioners daily, offering scientifically sound solutions supported by math, code examples, and practical demonstrations.
By engaging with the content actively, readers can test proposed solutions in their specific contexts. Authored by a renowned expert and portfolio manager, this book equips investment professionals with cutting-edge tools necessary to thrive in modern finance.
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