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Apache Spark Machine Learning Blueprints (Paperback)
Loot Price: R1,052
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Apache Spark Machine Learning Blueprints (Paperback)
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Develop a range of cutting-edge machine learning projects with
Apache Spark using this actionable guide About This Book *
Customize Apache Spark and R to fit your analytical needs in
customer research, fraud detection, risk analytics, and
recommendation engine development * Develop a set of practical
Machine Learning applications that can be implemented in real-life
projects * A comprehensive, project-based guide to improve and
refine your predictive models for practical implementation Who This
Book Is For If you are a data scientist, a data analyst, or an R
and SPSS user with a good understanding of machine learning
concepts, algorithms, and techniques, then this is the book for
you. Some basic understanding of Spark and its core elements and
application is required. What You Will Learn * Set up Apache Spark
for machine learning and discover its impressive processing power *
Combine Spark and R to unlock detailed business insights essential
for decision making * Build machine learning systems with Spark
that can detect fraud and analyze financial risks * Build
predictive models focusing on customer scoring and service ranking
* Build a recommendation systems using SPSS on Apache Spark *
Tackle parallel computing and find out how it can support your
machine learning projects * Turn open data and communication data
into actionable insights by making use of various forms of machine
learning In Detail There's a reason why Apache Spark has become one
of the most popular tools in Machine Learning - its ability to
handle huge datasets at an impressive speed means you can be much
more responsive to the data at your disposal. This book shows you
Spark at its very best, demonstrating how to connect it with R and
unlock maximum value not only from the tool but also from your
data. Packed with a range of project "blueprints" that demonstrate
some of the most interesting challenges that Spark can help you
tackle, you'll find out how to use Spark notebooks and access,
clean, and join different datasets before putting your knowledge
into practice with some real-world projects, in which you will see
how Spark Machine Learning can help you with everything from fraud
detection to analyzing customer attrition. You'll also find out how
to build a recommendation engine using Spark's parallel computing
powers. Style and approach This book offers a step-by-step approach
to setting up Apache Spark, and use other analytical tools with it
to process Big Data and build machine learning projects.The initial
chapters focus more on the theory aspect of machine learning with
Spark, while each of the later chapters focuses on building
standalone projects using Spark.
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