Introduction to NLP
Course overview
Technologies based on NLP are becoming increasingly widespread. The benefits of natural language processing are innumerable. Natural language processing can be leveraged by companies to improve the efficiency of documentation processes, enhance the accuracy of documentation, and identify the most pertinent information from large databases. For example, a hospital might use natural language processing to pull a specific diagnosis from a physician’s unstructured notes and assign a billing code.
This course provides an introduction to the field of Natural Language Processing. It includes relevant background material in Linguistics, Mathematics, Probabilities, and Computer Science. Some of the topics covered in the course are Text parsing, Regular Expression, Part of Speech Tagging, Semantics, Text Similarity, Sentiment Analysis, Text Classification, and Text Summarization.
What you'll learn
By digging into the material presented here, you will learn:
- How to manipulate and analyze language data
- How to use based concepts from NLP and linguistics for language understanding
- How to solve classification problems in NLP
- How to compare words, sentences, and text datasets
- How to resolve business problems by using NLP methods
Syllabus
WEEK 1. Introduction to NLP with Python
WEEK 2. Processing Raw Text
WEEK 3. Text classification
WEEK 4. Advances NLP