Book Image

Natural Language Processing with Python [Video]

By : Tyler Edwards
Book Image

Natural Language Processing with Python [Video]

By: Tyler Edwards

Overview of this book

NLP, or Natural Language Processing, is a computational approach to communication. This course will get you up-and-running with the popular NLP platform called Natural Language Toolkit (NLTK) in no time. You will start off by preparing text for Natural Language Processing by cleaning and simplifying it. Then you will implement more complex algorithms to break this text down and uncover contextual relationships that reveal the meaning and content of the text. You will learn how to tokenize various parts of sentences, and how to analyze them. You will learn about semantic as well as the syntactic analysis of text. During this course, you will learn how to solve various ambiguities in processing human language. You will also gain experience with NLP using Python and will be introduced to a variety of useful tools in NLTK. Plus, you will have an opportunity to build your first NLP application! By the end of this course, you will have the skills and tools to begin solving problems in the growing field of Latent Semantic Analysis The code files and all related files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Natural-Language-Processing-with-Python-Video-
Table of Contents (4 chapters)
Chapter 4
Latent Semantic Analysis
Content Locked
Section 3
Programming Example of Singular Value Decomposition
This section introduces the concept of dimensionality reduction and explains why it is used in the context of latent semantic analysis. An example problem is then worked out by importing the native NLTK Reuters dataset and performing dimensionality reduction using principal component analysis. - Import NLTK Reuters dataset - Perform count vectorization and tf-idf weighting - Create 2D representation of tf-idf feature space using SVD