Book Image

Natural Language Processing: Python and NLTK

By : Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi
Book Image

Natural Language Processing: Python and NLTK

By: Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi

Overview of this book

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: ? NTLK essentials by Nitin Hardeniya ? Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins ? Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur

Related Content you might be interested in

Current Title:

Small book image
Natural Language Processing: Python and NLTK
Jacob Perkins | Nitin Hardeniya | Deepti Chopra | Iti Mathur | Nisheeth Joshi
Nov, 2016 | 11 hours 42 minutes
No titles found
Table of Contents (6 chapters)
Preface
Preface
What this learning path covers
What you need for this learning path
Who this learning path is for
Reader feedback
Customer support
Free Chapter
1
1. Module 1
1. Module 1
1. Introduction to Natural Language Processing
2. Text Wrangling and Cleansing
3. Part of Speech Tagging
4. Parsing Structure in Text
5. NLP Applications
6. Text Classification
7. Web Crawling
8. Using NLTK with Other Python Libraries
9. Social Media Mining in Python
10. Text Mining at Scale
2
2. Module 2
2. Module 2
1. Tokenizing Text and WordNet Basics
2. Replacing and Correcting Words
3. Creating Custom Corpora
4. Part-of-speech Tagging
5. Extracting Chunks
6. Transforming Chunks and Trees
7. Text Classification
8. Distributed Processing and Handling Large Datasets
9. Parsing Specific Data Types
A. Penn Treebank Part-of-speech Tags
3
3. Module 3
3. Module 3
1. Working with Strings
2. Statistical Language Modeling
3. Morphology – Getting Our Feet Wet
4. Parts-of-Speech Tagging – Identifying Words
5. Parsing – Analyzing Training Data
6. Semantic Analysis – Meaning Matters
7. Sentiment Analysis – I Am Happy
8. Information Retrieval – Accessing Information
9. Discourse Analysis – Knowing Is Believing
10. Evaluation of NLP Systems – Analyzing Performance
4
B. Bibliography
B. Bibliography
5
Index
Index

Customer support

Now that you are the proud owner of a Packt course, we have a number of things to help you to get the most from your purchase.

Downloading the example code

You can download the example code files for this course from your account at http://www.packtpub.com. If you purchased this course elsewhere, you can visit http://www.packtpub.com/support and register to have the files e-mailed directly to you.

You can download the code files by following these steps:

  1. Log in or register to our website using your e-mail address and password.
  2. Hover the mouse pointer on the SUPPORT tab at the top.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the course in the Search box.
  5. Select the course for which you're looking to download the code files.
  6. Choose from the drop-down menu where you purchased this course from.
  7. Click on Code Download.

You can also download the code files by clicking on the Code Files button on the course's webpage at the Packt Publishing website. This page can be accessed by entering the course's name in the Search box. Please note that you need to be logged in to your Packt account.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR / 7-Zip for Windows
  • Zipeg / iZip / UnRarX for Mac
  • 7-Zip / PeaZip for Linux

The code bundle for the course is also hosted on GitHub at https://github.com/PacktPublishing/Natural-Language-Processing-Python-and-NLTK. We also have other code bundles from our rich catalog of books, videos and courses available at https://github.com/PacktPublishing/. Check them out!

Errata

Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you find a mistake in one of our books—maybe a mistake in the text or the code—we would be grateful if you could report this to us. By doing so, you can save other readers from frustration and help us improve subsequent versions of this course. If you find any errata, please report them by visiting http://www.packtpub.com/submit-errata, selecting your course, clicking on the Errata Submission Form link, and entering the details of your errata. Once your errata are verified, your submission will be accepted and the errata will be uploaded to our website or added to any list of existing errata under the Errata section of that title.

To view the previously submitted errata, go to https://www.packtpub.com/books/content/support and enter the name of the book in the search field. The required information will appear under the Errata section.

Piracy

Piracy of copyrighted material on the Internet is an ongoing problem across all media. At Packt, we take the protection of our copyright and licenses very seriously. If you come across any illegal copies of our works in any form on the Internet, please provide us with the location address or website name immediately so that we can pursue a remedy.

Please contact us at with a link to the suspected pirated material.

We appreciate your help in protecting our authors and our ability to bring you valuable content.

Questions

If you have a problem with any aspect of this course, you can contact us at , and we will do our best to address the problem.

Previous Section
Next Chapter