Nitin Hardeniya - NLTK Essentials
Here you can read online Nitin Hardeniya - NLTK Essentials full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2015, publisher: Packt Publishing, genre: Home and family. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:NLTK Essentials
- Author:
- Publisher:Packt Publishing
- Genre:
- Year:2015
- Rating:3 / 5
- Favourites:Add to favourites
- Your mark:
NLTK Essentials: summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "NLTK Essentials" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
Build cool NLP and machine learning applications using NLTK and other Python libraries
About This Book- Extract information from unstructured data using NLTK to solve NLP problems
- Analyse linguistic structures in text and learn the concept of semantic analysis and parsing
- Learn text analysis, text mining, and web crawling in a simplified manner
If you are an NLP or machine learning enthusiast with some or no experience in text processing, then this book is for you. This book is also ideal for expert Python programmers who want to learn NLTK quickly.
What You Will Learn- Get a glimpse of the complexity of natural languages and how they are processed by machines
- Clean and wrangle text using tokenization and chunking to help you better process data
- Explore the different types of tags available and learn how to tag sentences
- Create a customized parser and tokenizer to suit your needs
- Build a real-life application with features such as spell correction, search, machine translation and a question answering system
- Retrieve any data content using crawling and scraping
- Perform feature extraction and selection, and build a classification system on different pieces of texts
- Use various other Python libraries such as pandas, scikit-learn, matplotlib, and gensim
- Analyse social media sites to discover trending topics and perform sentiment analysis
Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, its becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool.
You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text.
By the end of this book, you will be confident about NLP and data science concepts and know how to apply them in your day-to-day work.
Nitin Hardeniya: author's other books
Who wrote NLTK Essentials? Find out the surname, the name of the author of the book and a list of all author's works by series.
NLTK Essentials — read online for free the complete book (whole text) full work
Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "NLTK Essentials" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.
Font size:
Interval:
Bookmark:
Copyright 2015 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: July 2015
Production reference: 1220715
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78439-690-9
www.packtpub.com
Author
Nitin Hardeniya
Reviewers
Afroz Hussain
Sujit Pal
Kumar Raj
Commissioning Editor
Kunal Parikh
Acquisition Editor
Kevin Colaco
Content Development Editor
Samantha Gonsalves
Technical Editor
Rohan Uttam Gosavi
Copy Editors
Neha Vyas
Brandt D'Mello
Samantha Lyon
Project Coordinator
Sanchita Mandal
Proofreader
Safis Editing
Indexer
Mariammal Chettiyar
Graphics
Disha Haria
Production Coordinator
Conidon Miranda
Cover Work
Conidon Miranda
Nitin Hardeniya is a data scientist with more than 4 years of experience working with companies such as Fidelity, Groupon, and [24]7-inc. He has worked on a variety of business problems across different domains. He holds a master's degree in computational linguistics from IIIT-H. He is the author of 5 patents in the field of customer experience.
He is passionate about language processing and large unstructured data. He has been using Python for almost 5 years in his day-to-day work. He believes that Python could be a single-point solution to most of the problems related to data science.
He has put on his hacker's hat to write this book and has tried to give you an introduction to all the sophisticated tools related to NLP and machine learning in a very simplified form. In this book, he has also provided a workaround using some of the amazing capabilities of Python libraries, such as NLTK, scikit-learn, pandas, and NumPy.
Afroz Hussain is a data scientist by profession and is currently associated with a US-based data science and ML start-up, PredictifyMe. He has experience of working on many data science projects and has extensive experience of Python, scikit-learn, and text mining with NLTK. He has more than 10 years of programming and software development experience along with the experience of working on data analysis and business intelligence projects. He has acquired new skills in data science by taking online courses and taking part in Kaggle competitions.
Sujit Pal works at Elsevier Labs, which is a research and development group within the Reed-Elsevier PLC group. His interests are in the fields of information retrieval, distributed processing, ontology development, natural language processing, and machine learning. He is also interested in and writes code in Python, Scala, and Java. He combines his skills in these areas in order to help build new features or feature improvements for different products across the company. He believes in lifelong learning and blogs about his experiences at sujitpal.blogspot.com.
Kumar Raj serves as a data scientist II at Hewlett-Packard Software solutions in the research and development department, where he is responsible for developing the analytics layer for core HP software products. He is a graduate from Indian Institute of Technology, Kharagpur, and has more than 2 years of experience in various big data analytics domains, namely text analytics, web crawling and scraping, HR analytics, virtualization system performance optimization, and climate change forecasting.
For support files and downloads related to your book, please visit www.PacktPub.com.
Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at > for more details.
At www.PacktPub.com, you can also read a collection of free technical articles, sign up for a range of free newsletters and receive exclusive discounts and offers on Packt books and eBooks.
https://www2.packtpub.com/books/subscription/packtlib
Do you need instant solutions to your IT questions? PacktLib is Packt's online digital book library. Here, you can search, access, and read Packt's entire library of books.
- Fully searchable across every book published by Packt
- Copy and paste, print, and bookmark content
- On demand and accessible via a web browser
If you have an account with Packt at www.PacktPub.com, you can use this to access PacktLib today and view 9 entirely free books. Simply use your login credentials for immediate access.
This book is about NLTK and how NLTK can be used in conjunction with other Python libraries. NLTK is one of the most popular and widely used libraries in the natural language processing (NLP) community. The beauty of NLTK lies in its simplicity, where most of the complex NLP tasks can be implemented by using a few lines of code.
The first half of this book starts with an introduction to Python and NLP. In this book, you'll learn a few generic preprocessing techniques, such as tokenization, stemming, and stop word removal, and some NLP-specific preprocessing, such as POS tagging and NER that are involved in most text-related NLP tasks. We gradually move on to more complex NLP tasks, such as parsing and other NLP applications.
The second half of this book focuses more on how some of the NLP applications, such as text classification, can be deployed using NLTK and scikit-learn. We talk about some other Python libraries that you should know about for text-mining-related or NLP-related tasks. We also look at data gathering from the Web and social media and how NLTK can be used on a large scale in this chapter.
, Introduction to Natural Language Processing , talks about some of the basic concepts in NLP and introduces you to NLTK and Python. This chapter focuses on getting you up to speed with NLTK and how to start with the installation of the required libraries to build one very basic word cloud example.
, Text Wrangling and Cleansing
Font size:
Interval:
Bookmark:
Similar books «NLTK Essentials»
Look at similar books to NLTK Essentials. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.
Discussion, reviews of the book NLTK Essentials and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.