Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge.

This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.

By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulated
in this book.

1137644955
Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge.

This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.

By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulated
in this book.

39.99 In Stock
Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

by Nataraj Dasgupta
Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

by Nataraj Dasgupta

eBook

$39.99 

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge.

This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.

By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulated
in this book.


Product Details

ISBN-13: 9781783554409
Publisher: Packt Publishing
Publication date: 01/15/2018
Sold by: Barnes & Noble
Format: eBook
Pages: 412
File size: 64 MB
Note: This product may take a few minutes to download.
From the B&N Reads Blog

Customer Reviews