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Scala Machine Learning Projects - Build real-world machine learning and deep learning projects with Scala (Paperback)
Loot Price: R1,324
Discovery Miles 13 240
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Scala Machine Learning Projects - Build real-world machine learning and deep learning projects with Scala (Paperback)
Expected to ship within 10 - 15 working days
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Powerful smart applications using deep learning algorithms to
dominate numerical computing, deep learning, and functional
programming. Key Features Explore machine learning techniques with
prominent open source Scala libraries such as Spark ML, H2O, MXNet,
Zeppelin, and DeepLearning4j Solve real-world machine learning
problems by delving complex numerical computing with Scala
functional programming in a scalable and faster way Cover all key
aspects such as collection, storing, processing, analyzing, and
evaluation required to build and deploy machine models on computing
clusters using Scala Play framework. Book DescriptionMachine
learning has had a huge impact on academia and industry by turning
data into actionable information. Scala has seen a steady rise in
adoption over the past few years, especially in the fields of data
science and analytics. This book is for data scientists, data
engineers, and deep learning enthusiasts who have a background in
complex numerical computing and want to know more hands-on machine
learning application development. If you're well versed in machine
learning concepts and want to expand your knowledge by delving into
the practical implementation of these concepts using the power of
Scala, then this book is what you need! Through 11 end-to-end
projects, you will be acquainted with popular machine learning
libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the
end, you will be able to use numerical computing and functional
programming to carry out complex numerical tasks to develop, build,
and deploy research or commercial projects in a production-ready
environment. What you will learn Apply advanced regression
techniques to boost the performance of predictive models Use
different classification algorithms for business analytics Generate
trading strategies for Bitcoin and stock trading using ensemble
techniques Train Deep Neural Networks (DNN) using H2O and Spark ML
Utilize NLP to build scalable machine learning models Learn how to
apply reinforcement learning algorithms such as Q-learning for
developing ML application Learn how to use autoencoders to develop
a fraud detection application Implement LSTM and CNN models using
DeepLearning4j and MXNet Who this book is forIf you want to
leverage the power of both Scala and Spark to make sense of Big
Data, then this book is for you. If you are well versed with
machine learning concepts and wants to expand your knowledge by
delving into the practical implementation using the power of Scala,
then this book is what you need! Strong understanding of Scala
Programming language is recommended. Basic familiarity with machine
Learning techniques will be more helpful.
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