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Mastering Java Machine Learning (Paperback)
Loot Price: R1,635
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Mastering Java Machine Learning (Paperback)
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Become an advanced practitioner with this progressive set of master
classes on application-oriented machine learning About This Book *
Comprehensive coverage of key topics in machine learning with an
emphasis on both the theoretical and practical aspects * More than
15 open source Java tools in a wide range of techniques, with code
and practical usage. * More than 10 real-world case studies in
machine learning highlighting techniques ranging from data
ingestion up to analyzing the results of experiments, all preparing
the user for the practical, real-world use of tools and data
analysis. Who This Book Is For This book will appeal to anyone with
a serious interest in topics in Data Science or those already
working in related areas: ideally, intermediate-level data analysts
and data scientists with experience in Java. Preferably, you will
have experience with the fundamentals of machine learning and now
have a desire to explore the area further, are up to grappling with
the mathematical complexities of its algorithms, and you wish to
learn the complete ins and outs of practical machine learning. What
You Will Learn * Master key Java machine learning libraries, and
what kind of problem each can solve, with theory and practical
guidance. * Explore powerful techniques in each major category of
machine learning such as classification, clustering, anomaly
detection, graph modeling, and text mining. * Apply machine
learning to real-world data with methodologies, processes,
applications, and analysis. * Techniques and experiments developed
around the latest specializations in machine learning, such as deep
learning, stream data mining, and active and semi-supervised
learning. * Build high-performing, real-time, adaptive predictive
models for batch- and stream-based big data learning using the
latest tools and methodologies. * Get a deeper understanding of
technologies leading towards a more powerful AI applicable in
various domains such as Security, Financial Crime, Internet of
Things, social networking, and so on. In Detail Java is one of the
main languages used by practicing data scientists; much of the
Hadoop ecosystem is Java-based, and it is certainly the language
that most production systems in Data Science are written in. If you
know Java, Mastering Machine Learning with Java is your next step
on the path to becoming an advanced practitioner in Data Science.
This book aims to introduce you to an array of advanced techniques
in machine learning, including classification, clustering, anomaly
detection, stream learning, active learning, semi-supervised
learning, probabilistic graph modeling, text mining, deep learning,
and big data batch and stream machine learning. Accompanying each
chapter are illustrative examples and real-world case studies that
show how to apply the newly learned techniques using sound
methodologies and the best Java-based tools available today. On
completing this book, you will have an understanding of the tools
and techniques for building powerful machine learning models to
solve data science problems in just about any domain. Style and
approach A practical guide to help you explore machine learning-and
an array of Java-based tools and frameworks-with the help of
practical examples and real-world use cases.
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