《深度学习》由全球知名的三位专家Ian Goodfellow、Yoshua Bengio 和Aaron Courville撰写，是深度学习领域奠基性的经典教材。全书的内容包括3个部分：第1部分介绍基本的数学工具和机器学习的概念，它们是深度学习的预备知识；第2部分系统深入地讲解现今已成熟的深度学习方法和技术；第3部分讨论某些具有前瞻性的方向和想法，它们被公认为是深度学习未来的研究重点。 《深度学习》适合各类读者阅读，包括相关专业的大学生或研究生，以及不具有机器学习或统计背景、但是想要快速补充深度学习知识，以便在实际产品或平台中应用的软件工程师。

详细介绍支持向量机、Boosting、最大熵、条件随机场等十个统计学习方法。

This second edition of "An Introduction to Predictive Maintenance" helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of "An Introduction to Predictive Maintenance" will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. A comprehensive introduction to a system of monitoring critical industrial equipment, it optimizes the availability of process machinery and greatly reduce the cost of maintenance. It provides the means to improve product quality, productivity and profitability of manufacturing and production plants.

《预测性文本挖掘基础》是文本挖掘这个迅速发展领域的入门性教材和指南。作为入门型读物，论述由浅入深、理论结合实践、语言风趣、样例详实，详细地分析和总结了该领域的研究现状及未来发展。深入地讨论了文档分类、信息检索、聚类与组织文档、信息提取、基于Web的数据源、预测与评价等方面提出的问题。作为互联网和云计算蓬勃发展时代，为关注海量非结构化信息处理的学习者了解文本挖掘研究前沿打开了一扇窗口。 特别邀请知名的台湾辅仁大学统计资讯系谢邦昌教授倾情作序，评价“这本书为文本挖掘入门最佳的书”。 《预测性文本挖掘基础》原版是计算机科学方向的一本国外教材，译本适用于计算机专业本科生和研究生作为关键教材，同时，对于IT专业人员和管理人员是一个重要的资源。