This section provides an overview of the program and introduces the fundamentals of Natural Language Processing through symbolic manipulation, including text cleaning, normalization, and tokenization. You'll then build a part of speech tagger using hidden Markov models.
Overview
Syllabus
- Intro to NLP
- Arpan will give you an overview of how to build a Natural Language Processing pipeline.
- Text Processing
- Learn to prepare text obtained from different sources for further processing, by cleaning, normalizing and splitting it into individual words or tokens.
- Spam Classifier with Naive Bayes
- In this section, you'll learn how to build a spam email classifier using the naive Bayes algorithm.
- Part of Speech Tagging with HMMs
- Learn Hidden Markov Models, and apply them to part-of-speech tagging, a very popular problem in Natural Language Processing.
- Project: Part of Speech Tagging
- In this project, you'll build a hidden Markov model for part of speech tagging with a universal tagset.
- (Optional) IBM Watson Bookworm Lab
- Learn how to build a simple question-answering agent using IBM Watson.
Taught by
Luis Serrano and Arpan Chakraborty
