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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Practical Machine Learning (Paperback)
Loot Price: R1,362
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Practical Machine Learning (Paperback)
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Tackle the real-world complexities of modern machine learning with
innovative, cutting-edge, techniques About This Book * Fully-coded
working examples using a wide range of machine learning libraries
and tools, including Python, R, Julia, and Spark * Comprehensive
practical solutions taking you into the future of machine learning
* Go a step further and integrate your machine learning projects
with Hadoop Who This Book Is For This book has been created for
data scientists who want to see machine learning in action and
explore its real-world application. With guidance on everything
from the fundamentals of machine learning and predictive analytics
to the latest innovations set to lead the big data revolution into
the future, this is an unmissable resource for anyone dedicated to
tackling current big data challenges. Knowledge of programming
(Python and R) and mathematics is advisable if you want to get
started immediately. What You Will Learn * Implement a wide range
of algorithms and techniques for tackling complex data * Get to
grips with some of the most powerful languages in data science,
including R, Python, and Julia * Harness the capabilities of Spark
and Hadoop to manage and process data successfully * Apply the
appropriate machine learning technique to address real-world
problems * Get acquainted with Deep learning and find out how
neural networks are being used at the cutting-edge of machine
learning * Explore the future of machine learning and dive deeper
into polyglot persistence, semantic data, and more In Detail
Finding meaning in increasingly larger and more complex datasets is
a growing demand of the modern world. Machine learning and
predictive analytics have become the most important approaches to
uncover data gold mines. Machine learning uses complex algorithms
to make improved predictions of outcomes based on historical
patterns and the behaviour of data sets. Machine learning can
deliver dynamic insights into trends, patterns, and relationships
within data, immensely valuable to business growth and development.
This book explores an extensive range of machine learning
techniques uncovering hidden tricks and tips for several types of
data using practical and real-world examples. While machine
learning can be highly theoretical, this book offers a refreshing
hands-on approach without losing sight of the underlying
principles. Inside, a full exploration of the various algorithms
gives you high-quality guidance so you can begin to see just how
effective machine learning is at tackling contemporary challenges
of big data. This is the only book you need to implement a whole
suite of open source tools, frameworks, and languages in machine
learning. We will cover the leading data science languages, Python
and R, and the underrated but powerful Julia, as well as a range of
other big data platforms including Spark, Hadoop, and Mahout.
Practical Machine Learning is an essential resource for the modern
data scientists who want to get to grips with its real-world
application. With this book, you will not only learn the
fundamentals of machine learning but dive deep into the
complexities of real world data before moving on to using Hadoop
and its wider ecosystem of tools to process and manage your
structured and unstructured data. You will explore different
machine learning techniques for both supervised and unsupervised
learning; from decision trees to Naive Bayes classifiers and linear
and clustering methods, you will learn strategies for a truly
advanced approach to the statistical analysis of data. The book
also explores the cutting-edge advancements in machine learning,
with worked examples and guidance on deep learning and
reinforcement learning, providing you with practical demonstrations
and samples that help take the theory-and mystery-out of even the
most advanced machine learning methodologies. Style and approach A
practical data science tutorial designed to give you an insight
into the practical application of machine learning, this book takes
you through complex concepts and tasks in an accessible way.
Featuring information on a wide range of data science techniques,
Practical Machine Learning is a comprehensive data science
resource.
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