Machine Learning with Spark

Couverture
Packt Publishing Ltd, 20 févr. 2015 - 338 pages
If you are a Scala, Java, or Python developer with an interest in machine learning and data analysis and are eager to learn how to apply common machine learning techniques at scale using the Spark framework, this is the book for you. While it may be useful to have a basic understanding of Spark, no previous experience is required.
 

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Table des matières

Preface
1
Getting Up and Running with Spark
7
Designing a Machine Learning System
37
Obtaining Processing and Preparing Data with Spark
51
Building a Recommendation Engine with Spark
83
Building a Classification Model with Spark
117
Building a Regression Model with Spark
161
Building a Clustering Model with Spark
197
Dimensionality Reduction with Spark
221
Advanced Text Processing with Spark
247
Realtime Machine Learning with Spark Streaming
279
Index
311
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À propos de l'auteur (2015)

Nick Pentreath has a background in financial markets, machine learning, and software development. He has worked at Goldman Sachs Group, Inc.; as a research scientist at the online ad targeting start-up Cognitive Match Limited, London; and led the Data Science and Analytics team at Mxit, Africa's largest social network. He is a cofounder of Graphflow, a big data and machine learning company focused on user-centric recommendations and customer intelligence. He is passionate about combining commercial focus with machine learning and cutting-edge technology to build intelligent systems that learn from data to add value to the bottom line. Nick is a member of the Apache Spark Project Management Committee.

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