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Mastering Text Mining with R

You're reading from Mastering Text Mining with R Extract and recognize your text data

Product type Paperback

Published in Dec 2016

Publisher Packt

ISBN-13 9781783551811

Length 258 pages

Edition 1st Edition

Languages

R

Concepts

Data Mining

Author (1):

KUMAR ASHISH

View More author details

Table of Contents (9) Chapters

Preface

1. Statistical Linguistics with R FREE CHAPTER

2. Processing Text

3. Categorizing and Tagging Text

4. Dimensionality Reduction

5. Text Summarization and Clustering

6. Text Classification

7. Entity Recognition

Index

What you need for this book

R 3.3.2 is tested on the following platforms:

Windows® 7.0 (SP1), 8.1, 10, Windows Server® 2008 R2 (SP1) and 2012
Ubuntu 14.04, 16.04
CentOS / Red Hat Enterprise Linux 6.5, 7.1
SUSE Linux Enterprise Server 11
Mavericks (10.9), Yosemite (10.10), El Capitan (10.11), Sierra (10.12)

The hardware specification required for this book is as follows:

Processor: Processor 64-bit processor with x86-compatible architecture (such as AMD64, Intel 64, x86-64, IA-32e, EM64T, or x64 chips). ARM chips, Itanium-architecture chips (also known as IA-64), and non-Intel Macs are not supported. Multiple-core chips are recommended.
Free disk space. 250 MB.
RAM. 1 GB required, 4 GB recommended.

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Authors (1)

KUMAR ASHISH

KUMAR ASHISH

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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