Introduction to Natural Language Processing

Course

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.

Advanced

2 weeks

Real-world Projects

Completion Certificate

Last Updated June 19, 2024

Prerequisites:

Neural network basics • Object-oriented programming basics • Deep learning framework proficiency

Course Lessons

Lesson 1

Intro to NLP

Arpan will give you an overview of how to build a Natural Language Processing pipeline.

Lesson 2

Text Processing

Learn to prepare text obtained from different sources for further processing, by cleaning, normalizing and splitting it into individual words or tokens.

Lesson 3

Spam Classifier with Naive Bayes

In this section, you'll learn how to build a spam email classifier using the naive Bayes algorithm.

Lesson 4

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.

Lesson 5 • Project

Project: Part of Speech Tagging

In this project, you'll build a hidden Markov model for part of speech tagging with a universal tagset.

Lesson 6

(Optional) IBM Watson Bookworm Lab

Learn how to build a simple question-answering agent using IBM Watson.

Taught By The Best

Luis Serrano

Instructor

Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.

Arpan Chakraborty

Instructor

Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.

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