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Books > Computing & IT > General theory of computing
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R Machine Learning By Example (Paperback)
Loot Price: R1,307
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R Machine Learning By Example (Paperback)
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Understand the fundamentals of machine learning with R and build
your own dynamic algorithms to tackle complicated real-world
problems successfully About This Book * Get to grips with the
concepts of machine learning through exciting real-world examples *
Visualize and solve complex problems by using power-packed R
constructs and its robust packages for machine learning * Learn to
build your own machine learning system with this example-based
practical guide Who This Book Is For If you are interested in
mining useful information from data using state-of-the-art
techniques to make data-driven decisions, this is a go-to guide for
you. No prior experience with data science is required, although
basic knowledge of R is highly desirable. Prior knowledge in
machine learning would be helpful but is not necessary. What You
Will Learn * Utilize the power of R to handle data extraction,
manipulation, and exploration techniques * Use R to visualize data
spread across multiple dimensions and extract useful features *
Explore the underlying mathematical and logical concepts that drive
machine learning algorithms * Dive deep into the world of analytics
to predict situations correctly * Implement R machine learning
algorithms from scratch and be amazed to see the algorithms in
action * Write reusable code and build complete machine learning
systems from the ground up * Solve interesting real-world problems
using machine learning and R as the journey unfolds * Harness the
power of robust and optimized R packages to work on projects that
solve real-world problems in machine learning and data science In
Detail Data science and machine learning are some of the top
buzzwords in the technical world today. From retail stores to
Fortune 500 companies, everyone is working hard to making machine
learning give them data-driven insights to grow their business.
With powerful data manipulation features, machine learning
packages, and an active developer community, R empowers users to
build sophisticated machine learning systems to solve real-world
data problems. This book takes you on a data-driven journey that
starts with the very basics of R and machine learning and gradually
builds upon the concepts to work on projects that tackle real-world
problems. You'll begin by getting an understanding of the core
concepts and definitions required to appreciate machine learning
algorithms and concepts. Building upon the basics, you will then
work on three different projects to apply the concepts of machine
learning, following current trends and cover major algorithms as
well as popular R packages in detail. These projects have been
neatly divided into six different chapters covering the worlds of
e-commerce, finance, and social-media, which are at the very core
of this data-driven revolution. Each of the projects will help you
to understand, explore, visualize, and derive insights depending
upon the domain and algorithms. Through this book, you will learn
to apply the concepts of machine learning to deal with data-related
problems and solve them using the powerful yet simple language, R.
Style and approach The book is an enticing journey that starts from
the very basics to gradually pick up pace as the story unfolds.
Each concept is first defined in the larger context of things
succinctly, followed by a detailed explanation of their
application. Each topic is explained with the help of a project
that solves a real real-world problem involving hands-on work thus
giving you a deep insight into the world of machine learning.
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