Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You’ll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the a...(展开全部)

It's been said that data is the new "dirt"—the raw material from which and on which you build the structures of the modern world. And like dirt, data can seem like a limitless, undifferentiated mass. The ability to take raw data, access it, filter it, process it, visualize it, understand it, and communicate it to others is possibly the most essential business problem for the co...(展开全部)

It's been said that data is the new "dirt"—the raw material from which and on which you build the structures of the modern world. And like dirt, data can seem like a limitless, undifferentiated mass. The ability to take raw data, access it, filter it, process it, visualize it, understand it, and communicate it to others is possibly the most essential business problem for the co...(展开全部)

From the author of a world bestseller published in eleven languages, The Hundred-Page Machine Learning Book, this new book by Andriy Burkov is the most complete applied AI book out there. It is filled with best practices and design patterns of building reliable machine learning solutions that scale. Andriy Burkov has a Ph.D. in AI and is the leader of a machine learning team at...(展开全部)

This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market's past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that ar...(展开全部)

特征工程对于应用机器学习来说是基础的，但是使用域知识来加强你的预测模型既困难成本又高。为了弥补特征工程现有资料的不足，本书将会为初中级数据科学家讲解如何处理这项广泛应用却鲜见讨论的技术。 作者Alic Zheng会讲解常用的练习和数学原理，以帮助工程师分析新数据和任务的特征。如果你理解基本的机器学习概念，如有监督学习和无监督学习，那么你已经准备好学习本书了。你不仅会学习到如何以一种系统化和原理化的方式部署特征工程，并且还会学习如何更好地实践数据科学。

特征工程对于应用机器学习来说是基础的，但是使用域知识来加强你的预测模型既困难成本又高。为了弥补特征工程现有资料的不足，本书将会为初中级数据科学家讲解如何处理这项广泛应用却鲜见讨论的技术。 作者Alic Zheng会讲解常用的练习和数学原理，以帮助工程师分析新数据和任务的特征。如果你理解基本的机器学习概念，如有监督学习和无监督学习，那么你已经准备好学习本书了。你不仅会学习到如何以一种系统化和原理化的方式部署特征工程，并且还会学习如何更好地实践数据科学。

Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you’ll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you’ll work with core algorithms, including deep...(展开全部)

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable...(展开全部)

A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing. Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited ...(展开全部)