etc的专栏

知识大迁移 英文版 Head in the Cloud.epub 《知识大迁移》解读了信息时代的致胜关键！首先，作者剖析了在信息爆炸的时代，人们为什么变得越来越无知，还意识不到自己的无知；其次，通过覆盖全美的调查和研究，以大数据的形式揭示了知识与收入之间的关系，告诉大家学习哪些知识可以更富有、更幸福；最后，作者告诉我们，如何利用现有的媒体、网络等资源，在移动知识时代成为真正的赢家。

The Definitive Guide to Java Platform Best Practices—Updated for Java 7, 8, and 9 Java has changed dramatically since the previous edition of Effective Java was published shortly after the release of Java 6. This Jolt award-winning classic has now been thoroughly updated to take full advantage of the latest language and library features. The support in modern Java for multiple paradigms increases the need for specific best-practices advice, and this book delivers. As in previous editions, each chapter of Effective Java, Third Edition, consists of several “items,” each presented in the form of a short, stand-alone essay that provides specific advice, insight into Java platform subtleties, and updated code examples. The comprehensive descriptions and explanations for each item illuminate what to do, what not to do, and why. The third edition covers language and library features added in Java 7, 8, and 9, including the functional programming constructs that were added to its object-oriented roots. Many new items have been added, including a chapter devoted to lambdas and streams. New coverage includes Functional interfaces, lambda expressions, method references, and streams Default and static methods in interfaces Type inference, including the diamond operator for generic types The @SafeVarargs annotation The try-with-resources statement New library features such as the Optional interface, java.time, and the convenience factory methods for collections

This third edition of John Zelle's Python Programming continues the tradition of updating the text to reflect new technologies while maintaining a time-tested approach to teaching introductory computer science. An important change to this edition is the removal of most uses of eval and the addition of a discussion of its dangers. In our increasingly connected world, it's never too early to begin considering computer security issues. This edition also uses several new graphics examples, developed throughout chapters 4-12.

Welcome to Learning Elasticsearch. We will start by describing the basics concepts and discuss how Elasticsearch handles failures and ensures high availability. You will see how to install Elasticsearch and Kibana and learn how to index and update your data. We will use an e-commerce site as an example to explain how a search engine works and how to query your data. The real power of Elasticsearch is aggregations. You will see how to perform aggregation-based analytics with ease. You will also see how to use Kibana to explore and visualize your data. Finally, we will discuss how to use Graph to discover relations in your data and use alerting to set up alerts and notification on different trends in your data.

Book Description Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you’ll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton’s more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. ◦Illustrates cost-benefit evaluation of potential projects ◦Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools ◦Approachable reference can be read from cover to cover by readers of all experience levels ◦Includes practical examples and case studies as well as actionable business insights from author’s own experience Table of Contents Chapter 1. Introduction Chapter 2. Business Objectives Chapter 3. Data Quality Chapter 4. Data Representation Chapter 5. Possible Sources of Data and Information Chapter 6. Selection of variables and factors Chapter 7. Data Sampling Chapter 8. Data Analysis Chapter 9. Modeling Chapter 10. The Data Mart – structured data warehouse Chapter 11. Querying, Report Generation and Executive Information Systems Chapter 12. Analytical CRM – Customer Relationship Analysis Chapter 13. Website analysis and Internet search Chapter 14. Online social network analysis Chapter 15. Web search trend analysis Chapter 16. Creating your own environment for commercial data analysis Chapter 17. Summary Book Details ◦Paperback: 304 pages ◦Publisher: Morgan Kaufmann (February 2014) ◦Language: English ◦ISBN-10: 0124166024 ◦ISBN-13: 978-0124166028