Advanced Analytics with Spark: Patterns for Learning from Data at Scale
Author:   Sandy Ryza ,  Uri Laserson ,  Sean Owens ,  Josh Wills
Publisher:   O'Reilly Media
Edition:   2nd Revised edition
ISBN:  

9781491972953


Pages:   280
Publication Date:   23 June 2017
Format:   Paperback
Availability:   In Print   Availability explained
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Advanced Analytics with Spark: Patterns for Learning from Data at Scale


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Author:   Sandy Ryza ,  Uri Laserson ,  Sean Owens ,  Josh Wills
Publisher:   O'Reilly Media
Imprint:   O'Reilly Media
Edition:   2nd Revised edition
Dimensions:   Width: 17.80cm , Height: 1.50cm , Length: 23.30cm
Weight:   0.666kg
ISBN:  

9781491972953


ISBN 10:   1491972955
Pages:   280
Publication Date:   23 June 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Juliet Hougland is the Head of Data Science, Engineering at Cloudera. Juliet holds an MS in Applied Mathematics from University of Colorado, Boulder and graduated Phi Beta Kappa from Reed College with a BA in Math-Physics. Uri Laserson is an Assistant Professor of Genetics at the Icahn School of Medicine at Mount Sinai, where he develops scalable technology for genomics and immunology using the Hadoop ecosystem. Sean Owen is Director of Data Science at Cloudera. He is an ApacheSpark committer and PMC member, and was an Apache Mahout committer. Sandy Ryza is a data science lead at Clover Health. Prior, he was a senior data scientist at Cloudera. He is an Apache Spark committer, Apache Hadoop PMC member, and founder of the Time Series for Spark project. He holds the Brown University computer science department's 2012 Twining award for ""Most Chill."" Josh Wills is the Head of Data Engineering at Slack, the founder of the Apache Crunch project, and wrote a tweet about data scientists once.

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