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A hands-on guide for professionals to perform various data science
tasks in R Key Features Explore the popular R packages for data
science Use R for efficient data mining, text analytics and feature
engineering Become a thorough data science professional with the
help of hands-on examples and use-cases in R Book DescriptionR is
the most widely used programming language, and when used in
association with data science, this powerful combination will solve
the complexities involved with unstructured datasets in the real
world. This book covers the entire data science ecosystem for
aspiring data scientists, right from zero to a level where you are
confident enough to get hands-on with real-world data science
problems. The book starts with an introduction to data science and
introduces readers to popular R libraries for executing data
science routine tasks. This book covers all the important processes
in data science such as data gathering, cleaning data, and then
uncovering patterns from it. You will explore algorithms such as
machine learning algorithms, predictive analytical models, and
finally deep learning algorithms. You will learn to run the most
powerful visualization packages available in R so as to ensure that
you can easily derive insights from your data. Towards the end, you
will also learn how to integrate R with Spark and Hadoop and
perform large-scale data analytics without much complexity. What
you will learn Understand the R programming language and its
ecosystem of packages for data science Obtain and clean your data
before processing Master essential exploratory techniques for
summarizing data Examine various machine learning prediction,
models Explore the H2O analytics platform in R for deep learning
Apply data mining techniques to available datasets Work with
interactive visualization packages in R Integrate R with Spark and
Hadoop for large-scale data analytics Who this book is forIf you
are a budding data scientist keen to learn about the popular pandas
library, or a Python developer looking to step into the world of
data analysis, this book is the ideal resource you need to get
started. Some programming experience in Python will be helpful to
get the most out of this course
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