Agile Data Science: Building Data Analytics Applications with Hadoop
A Science, Reference, Computer Science book. Building and maintaining consensus while collaborating is the hardest part of building software. Russell Jurney, Agile Data...
Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop.Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in...
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- Filetype: PDF
- Pages: 178 pages
- ISBN: 9781449326265 / 0
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More About Agile Data Science: Building Data Analytics Applications with Hadoop
Building and maintaining consensus while collaborating is the hardest part of building software. Russell Jurney, Agile Data Science: Building Data Analytics Applications with Hadoop //
Agile Data Science sets out to explain how to apply agile methodology in the field of data science. I would have liked more information on team formation and work processes, which the book covers pretty briefly. Instead the author focuses more on the tools (some of which are pretty dated at the time of reading) and one illustrative... One of the problems with data science is that any description of what is encountered takes on the appearance of a mythical unicorn, noone person could possibly have all of the skills required. And it gets worse when you add to the standard set of statistics, domain knowledge, and programming the ability to deploy the application into... It is a very short book. However, the overall idea on doing date science within agile approach was clear. I found most of the chapters very brief.
