R Data Analysis Cookbook, Second Edition: Customizable R Recipes for data mining, data visualization and time series analysis , Second Edition

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Key benefits

Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes

Find meaningful insights from your data and generate dynamic reports

A practical guide to help you put your data analysis skills in R to practical use

Description

Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way. By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios.

Who is this book for?

This book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed.

What you will learn

Acquire, format and visualize your data using R

Using R to perform an Exploratory data analysis

Introduction to machine learning algorithms such as classification and regression

Get started with social network analysis

Generate dynamic reporting with Shiny

Get started with geospatial analysis

Handling large data with R using Spark and MongoDB

Build Recommendation system- Collaborative Filtering, Content based and Hybrid

Learn real world dataset examples- Fraud Detection and Image Recognition

What do you get with Print?

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R Data Analysis Cookbook, Second Edition

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What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

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Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

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Leonardo Damasceno Dec 11, 2017

Did not like. Too superficial. Treat each topic as 'cake recipe'.

Amazon Verified review

Dimitri Shvorob Dec 07, 2017

Looking at the five-star reviews, I notice that "John DCousta" has only reviewed, and given five-star reviews, to Ganguly's two (Packt) books, and "Alessandro Breschi" - whose profile initially had name "Sunith Shetty" - has similarly only reviewed, and given five-star reviews, to three Packt books, one of them plagiarized. In all likelihood, both reviews are fake. Another thing you should know is that Ganguly's other book, "Learning Generative Adversarial Networks", is plagiarized. Even if this one isn't - which I think is unlikely - you should not support a plagiarist by buying his books.

John DCousta Oct 16, 2017

This book is for data analyst and aspiring data science professionals who are familiar with basics of R and want to expand their skill set in data analysis activities (without diving too much into mathematics/statistical jargon)- data cleaning & munging, eda, machine learning such as- regression, classification, advance clustering, deep learning (image recognition), handling large dataset in R with Spark.

Amazon Customer Oct 02, 2017

The R Data Analysis Cookbook 2nd Edition is primarily focused on real life data analysis and data science activities performed by data analyst/data scientist using R and offers succinct examples on a variety of data analysis topics such as data cleaning & munging, exploratory analysis, vectorized operations, regression, classification, advance clustering, deep learning (image recognition), geospatial analysis, social network analysis, handling large dataset in R with Spark and MongoDB. I enjoyed the section dealing with classification, image recognition and R with distrbuted system. This book does not provide introduction to R language (as it assume the readers to have basic knowledge in R as prerequisite). Although the book provide brief explanation of the machine learning algorithms used in the recipes, with equation, how it works along with its pros/cons, but it doesn't explain in details or great depth about each of the machine learning algorthim. For such information, you will have to look elsewhere such as "Beginning R Programming" and "Machine Learning: An Algorithmic Perspective". Overall it a very good book and hits the road running, if you just have basic knowledge of R programming.

R Data Analysis Cookbook, Second Edition: Customizable R Recipes for data mining, data visualization and time series analysis , Second Edition

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