Natural Language Processing with Python [Video]

More Information
  • Installing and setting up NLTK, and how to implement simple NLP tasks
  • The foundational concepts of part-of-speech tagging
  • Stemming, lemmatization, and named-entity recognition (NER)
  • Discover how to create frequency distributions on your text with NLTK
  • Analyze text and classify it into different categories
  • Use functions to implement concordance, similarity, dispersion plotting, and counting in NLTK to easily mine information from large heaps of textual data
  • Build your own movie review sentiment application in Python
  • Learn how to classify user reviews as positive or negative with sentiment analysis
  • See how your application, based on bag-of-words, can retrieve meaningful information
  • Apply Latent Semantic Analysis to extract the meaning of the text in response to user queries
  • Use Long Shot Term Memory to analyze sequential data in your NLP applications

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

Style and Approach

This video course covers various topics in Natural Language Processing, ranging from an introduction to the relevant Python libraries to applying specific linguistics concepts while exploring text datasets. It is evenly-paced for simplicity and does not require prior knowledge of NLP theory.

  • Comprehensive guide showing how textual data can be analyzed using the Natural Language Toolkit (NLTK)
  • Build your own NLP applications, such as a sentiment analyzer, and learn how to carry out information extraction on text datasets
  • Discover how Natural Language Processing can be used to investigate contextual relationships in human language
Course Length 1 hour 47 minutes
ISBN 9781787286085
Date Of Publication 29 Dec 2017


Tyler Edwards

Tyler Edwards is a senior engineer and software developer with over a decade of experience creating analysis tools in the space, defense, and nuclear industries. Tyler is experienced using a variety of programming languages (Python, C++, and more), and his research areas include machine learning, artificial intelligence, engineering analysis, and business analytics. Tyler holds a Master of Science degree in Mechanical Engineering from Ohio University. Looking forward, Tyler hopes to mentor students in applied mathematics, and demonstrate how data collection, analysis, and post-processing can be used to solve difficult problems and improve decision making.