Hands-on Data Science with R deals with the practical aspects of R development, more so than the theoretical. In other words, emphasis has been given on how to use R for different data science-related activities, such as machine learning and data mining, as well as topics in visualization, cloud computing, and others. Note that much of the book assumes some prior familiarity with R, such that it is intended for intermediate R users. While a number of introductory explanations, such as instructions for installing R Studio, have been provided, the reader may find some topics more advanced, which necessitates prior experience with R programming.
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Book Overview & Buying
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Table Of Contents
Hands-On Data Science with R
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Hands-On Data Science with R
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Overview of this book
R 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.
Table of Contents (16 chapters)
Preface
Free Chapter
Getting Started with Data Science and R
Descriptive and Inferential Statistics
Data Wrangling with R
KDD, Data Mining, and Text Mining
Data Analysis with R
Machine Learning with R
Forecasting and ML App with R
Neural Networks and Deep Learning
Markovian in R
Visualizing Data
Going to Production with R
Large Scale Data Analytics with Hadoop
The Road Ahead
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