Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark Contributor(s): Jurney, Russell (Author) |
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ISBN: 1491960116 ISBN-13: 9781491960110 Publisher: O'Reilly Media
WE WILL NOT BE UNDERSOLD! Click here for our low price guarantee Binding Type: Paperback - See All Available Formats & Editions Published: July 2017 |
Additional Information |
BISAC Categories: - Computers | Databases - Data Mining - Computers | Programming Languages - Javascript - Computers | Data Modeling & Design |
Physical Information: 0.7" H x 7" W x 9.1" L (1.20 lbs) 349 pages |
Features: Price on Product |
Descriptions, Reviews, Etc. |
Publisher Description: Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they're to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You'll learn an iterative approach that lets you quickly change the kind of analysis you're doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization.
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Contributor Bio(s): Jurney, Russell: - Russell Jurney runs a boutique consultancy, Data Syndrome, specializing in building analytics products. He cut his data teeth in casino gaming, building web apps to analyze the performance of slot machines in the US and Mexico. After dabbling in entrepreneurship, interactive media and journalism, he moved to silicon valley to build analytics applications at scale at Ning and LinkedIn. He lives on the ocean, in the fog, in Pacifica, California with Bella the Data Dog. |
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