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Principles of Data Science (Paperback)
Loot Price: R1,338
Discovery Miles 13 380
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Principles of Data Science (Paperback)
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Learn the techniques and math you need to start making sense of
your data About This Book * Enhance your knowledge of coding with
data science theory for practical insight into data science and
analysis * More than just a math class, learn how to perform
real-world data science tasks with R and Python * Create actionable
insights and transform raw data into tangible value Who This Book
Is For You should be fairly well acquainted with basic algebra and
should feel comfortable reading snippets of R/Python as well as
pseudo code. You should have the urge to learn and apply the
techniques put forth in this book on either your own data sets or
those provided to you. If you have the basic math skills but want
to apply them in data science or you have good programming skills
but lack math, then this book is for you. What You Will Learn * Get
to know the five most important steps of data science * Use your
data intelligently and learn how to handle it with care * Bridge
the gap between mathematics and programming * Learn about
probability, calculus, and how to use statistical models to control
and clean your data and drive actionable results * Build and
evaluate baseline machine learning models * Explore the most
effective metrics to determine the success of your machine learning
models * Create data visualizations that communicate actionable
insights * Read and apply machine learning concepts to your
problems and make actual predictions In Detail Need to turn your
skills at programming into effective data science skills?
Principles of Data Science is created to help you join the dots
between mathematics, programming, and business analysis. With this
book, you'll feel confident about asking-and answering-complex and
sophisticated questions of your data to move from abstract and raw
statistics to actionable ideas. With a unique approach that bridges
the gap between mathematics and computer science, this books takes
you through the entire data science pipeline. Beginning with
cleaning and preparing data, and effective data mining strategies
and techniques, you'll move on to build a comprehensive picture of
how every piece of the data science puzzle fits together. Learn the
fundamentals of computational mathematics and statistics, as well
as some pseudocode being used today by data scientists and
analysts. You'll get to grips with machine learning, discover the
statistical models that help you take control and navigate even the
densest datasets, and find out how to create powerful
visualizations that communicate what your data means. Style and
approach This is an easy-to-understand and accessible tutorial. It
is a step-by-step guide with use cases, examples, and illustrations
to get you well-versed with the concepts of data science. Along
with explaining the fundamentals, the book will also introduce you
to slightly advanced concepts later on and will help you implement
these techniques in the real world.
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