RapidMiner is one of the most widely used open source data mining solutions world-wide. This book provides an application use case-based introduction to data mining and to RapidMiner (and RapidAnalytics.) It presents many different applications of data mining and how to implement them with RapidMiner, and it allows readers to get started with their own data mining applications with RapidMiner, or other similar tools. The software, the data sets, and RapidMiner data mining processes used and discussed in the book are made available to readers.

《Keras快速上手：基于Python的深度学习实战》系统地讲解了深度学习的基本知识、建模过程和应用，并以深度学习在推荐系统、图像识别、自然语言处理、文字生成和时间序列中的具体应用为案例，详细介绍了从工具准备、数据获取和处理到针对问题进行建模的整个过程和实践经验，是一本非常好的深度学习入门书。 不同于许多讲解深度学习的书籍，《Keras快速上手：基于Python的深度学习实战》以实用为导向，选择了 Keras 作为编程框架，强调简单、快速地设计模型，而不去纠缠底层代码，使得内容相当易于理解，读者可以在 CNTK、 TensorFlow 和 Theano 的后台之间随意切换，非常灵活。并且本书能帮助读者从高度抽象的角度去审视业务问题，达到事半功倍的效果。

Review "A must-read resource for anyone who is serious about embracing the opportunity of big data." -- Craig Vaughan Global Vice President at SAP "This book goes beyond data analytics 101. It's the essential guide for those of us (all of us?) whose businesses are built on the ubiquity of data opportunities and the new mandate for data-driven decision-making." --Tom Phillips CEO of Media6Degrees and Former Head of Google Search and Analytics "Data is the foundation of new waves of productivity growth, innovation, and richer customer insight. Only recently viewed broadly as a source of competitive advantage, dealing well with data is rapidly becoming table stakes to stay in the game. The authors' deep applied experience makes this a must read--a window into your competitor's strategy." -- Alan Murray Serial Entrepreneur; Partner at Coriolis Ventures "This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data." -- Ron Bekkerman Chief Data Officer at Carmel Ventures "A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books." -- Ronny Kohavi Partner Architect at Microsoft Online Services Division About the Author Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing. Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standard reading in data science.

本书作者基于真实商业情景组织全书内容，书中囊括了几十个不同的行业和平台，提供了很多实用有效的可视化案例。当你需要创建有效的商业仪表盘时，本书可以为你提供全面可信的参考。 除了真实的商业情景之外，本书还用一部分内容解释了许多你在数据分析工作中将会遇到的问题。比如，当有人希望你能做出带有气泡和甜甜圈的“酷炫”仪表盘时，你会怎么做？ 设计良好的仪表盘必然可以显示出数据潜藏的风险、机遇以及更多的信息；但设计不良的仪表盘不仅可能会让仪表盘变得毫无用处，甚至还会产生误导。这本书提供的工具、指导和模型，不仅可以让仪表盘呈现所有的信息，还能使其生动有趣，富有启发性，让使用者产生参与感。 本书的几位作者都是有着30多年实操经验的权威专家，他们曾帮助数百个组织创建了有效的数据可视化工具，为很多实际问题提供了最佳解决方案。他们完全能够理解你在工作中将会遇到什么样的问题，并帮助你在数据可视化领域做到游刃有余。

本书由实战经验丰富的两位数据分析师执笔，首先介绍了商业领域里通用的数据分析框架，然后根据该框架，结合8个真实的案例，详细解说了通过数据分析解决各种商业问题的流程，让读者在解决问题的过程中学习各种数据分析方法，包括柱状图、交叉列表统计、A/B测试、多元回归分析、逻辑回归分析、主成分分析、聚类、决策树分析、机器学习等。特别是书中使用的数据都是未经清洗的原始数据，能够让读者了解真实的数据分析流程，避免纸上谈兵。