Agile Data: Building Data Analytics Applications

[Prohibitive]

English | March 22, 2013 | ISBN: 1449326269 | 250 Pages | PDF | 15.6 MB

Mining data requires a deep investment in people and time. How can you be sure you're building the right models? What tools help you connect with the customer's needs? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications.

English | March 22, 2013 | ISBN: 1449326269 | 250 Pages | PDF | 15.6 MB

Mining data requires a deep investment in people and time. How can you be sure you're building the right models? What tools help you connect with the customer's needs? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications.

Agile Data shows you how to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) javascript library. You'll learn an iterative approach that allows you to quickly change the kind of analysis you're doing, as you discover what the data is telling you. All the example code in this book is available as working Heroku apps.
Build an application to mine your own email inbox
Use several data structures to extract multiple features from a single dataset, and learn how different perspectives can yield insight
Rapidly boot your applications as simple front-ends to key/value stores
Add features driven by descriptive and inferential statistics, machine learning, and data visualization
Gather usage data and talk to real users to help guide your data-driven exploration

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