Learn to build expert NLP and machine learning projects using NLTK and other Python libraries
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
The scope of natural language complexity and how they are processed by machines
Clean and wrangle text using tokenization and chunking to help you process data better
Tokenize text into sentences and sentences into words
Classify text and perform sentiment analysis
Implement string matching algorithms and normalization techniques
Understand and implement the concepts of information retrieval and text summarization
Find out how to implement various NLP tasks in Python
Edition: 1st Edition
ISBN: 978-1787285101
Posted on: 12/8/2016
Format: Pdf
Page Count: 687 Pages
Author: Nitin Hardeniya,: --------------------
