Natural Language Processing

SPECIALIZATION ELECTIVE

Credit Hours : 3

Synopsis

Natural Language Processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics that deals with the development of systems that can process and understand human language. This course covers the entire life cycle of a typical NLP project - from data collection to model deployment and monitoring. Students will learn to understand the wide range of problems, tasks, and solution approaches in NLP. This includes the application of machine learning techniques in the implementation and evaluation of various NLP applications in domains such as e-commerce, healthcare and social media.

Course Content

Introduction to NLP
NLP General Pipeline

Text Extraction and Cleanup
Text Pre-Processing
Feature Engineering
NLP Modelling
NLP Evaluation

3. Text Representation

Vector Space Models
Vectorization Approaches
Distributed Representations
Text Similarity

4. Text Classification

Pipeline of Text Classification
Classifiers
Embedding in Text Classification
Evaluation and Interpretation of Text Classification Models

5. Information Extraction

Pipeline for IE
Keyphrase Extraction
Named Entity Recognition
Evaluation of IE Process

6. (Optional) Chatbots

Pipeline for Building Dialog Systems
Components of Dialog Systems
Evaluation Metrics

7. NLP Applications

NLP in Social Media (Sentiment Analysis)
NLP in E-Commerce (Product Reviews)
NLP in Healthcare

References

“Practical Natural Language Processing – A Comprehensive Guide to Building Real-World NLP System”, O’Reilly Media Inc., Published in June 2020

Prepared By

Ts. Dr. Nik Adilah Hanin Zahri

Page updated

Report abuse