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Books > Computing & IT > Applications of computing > Databases
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Mastering Java for Data Science (Paperback)
Loot Price: R1,414
Discovery Miles 14 140
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Mastering Java for Data Science (Paperback)
Expected to ship within 10 - 15 working days
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Use Java to create a diverse range of Data Science applications and
bring Data Science into production About This Book * An overview of
modern Data Science and Machine Learning libraries available in
Java * Coverage of a broad set of topics, going from the basics of
Machine Learning to Deep Learning and Big Data frameworks. *
Easy-to-follow illustrations and the running example of building a
search engine. Who This Book Is For This book is intended for
software engineers who are comfortable with developing Java
applications and are familiar with the basic concepts of data
science. Additionally, it will also be useful for data scientists
who do not yet know Java but want or need to learn it. If you are
willing to build efficient data science applications and bring them
in the enterprise environment without changing the existing stack,
this book is for you! What You Will Learn * Get a solid
understanding of the data processing toolbox available in Java *
Explore the data science ecosystem available in Java * Find out how
to approach different machine learning problems with Java * Process
unstructured information such as natural language text or images *
Create your own search engine * Get state-of-the-art performance
with XGBoost * Learn how to build deep neural networks with
DeepLearning4j * Build applications that scale and process large
amounts of data * Deploy data science models to production and
evaluate their performance In Detail Java is the most popular
programming language, according to the TIOBE index, and it is a
typical choice for running production systems in many companies,
both in the startup world and among large enterprises. Not
surprisingly, it is also a common choice for creating data science
applications: it is fast and has a great set of data processing
tools, both built-in and external. What is more, choosing Java for
data science allows you to easily integrate solutions with existing
software, and bring data science into production with less effort.
This book will teach you how to create data science applications
with Java. First, we will revise the most important things when
starting a data science application, and then brush up the basics
of Java and machine learning before diving into more advanced
topics. We start by going over the existing libraries for data
processing and libraries with machine learning algorithms. After
that, we cover topics such as classification and regression,
dimensionality reduction and clustering, information retrieval and
natural language processing, and deep learning and big data.
Finally, we finish the book by talking about the ways to deploy the
model and evaluate it in production settings. Style and approach
This is a practical guide where all the important concepts such as
classification, regression, and dimensionality reduction are
explained with the help of examples.
General
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