本书最大特点是很薄，看起来没有什么负担。可以找一个周末的下午，一边看，一边照做，一个下午就把书看完，这本书的所有例子跑完了。这本书的作用是通过实战让你培养TDD的思路。

Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science) By 作者: Jun Zhao – Wei Wang – Chunyang Sheng ISBN-10 书号: 3319940503 ISBN-13 书号: 9783319940502 Edition 版本: 1st ed. 2018 Release Finelybook 出版日期: 2018-08-20 pages 页数: (443） Springer出版超清 This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

Test-driven development by example

VLDB2021最新《数据增强机器学习》教程，194页ppt阐述知识库的完整性、召回与否定 VLDB会议全称International Conference on Very Large Date Bases，是数据库领域的顶级学术会议和另外两大数据库会议SIGMOD、ICD共同构成了数据库领域的三大顶级会议。本教程讲述数据增强机器学习相关主题。 近年来，我们看到了新的数据增强(DA)技术的发展，用于创建基于机器学习的解决方案所需的额外训练数据。在本教程中，我们将全面概述由数据管理社区开发的用于数据准备和数据集成的技术。除了调查利用规则、转换和外部知识创建额外训练数据的特定任务DA操作符之外，我们还探索了高级DA技术，如插值、条件生成和DA策略学习。最后，我们描述了数据挖掘与其他机器学习范式(如主动学习、预训练和弱监督学习)之间的联系。我们希望这一讨论能够为高质量数据集创建的整体数据增强框架的未来研究方向提供启示。

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