Natural Language Processing
Course Webpage for the semester Autumn 2023
Update!
1. Pretrained Transformers Slides have been uploaded.
Course Description
Natural language processing (NLP) refers to the branch of computer science, more specifically, the branch of artificial intelligence or AI concerned with giving computers the ability to understand text and spoken words as human beings can.
Syllabus
Introduction
Empirical laws etc.
Language Modeling: N-grams, smoothing
Distributional Semantics, Word Embeddings
Parts of Speech Tagging
Syntax, Dependency Parsing
RNNs and seq2seq models
Transformers, ELMO, BERT
Information Extraction: Relation Extraction
Special topic (LLMs, Dialogue Systems, Prompt Engineering)
Class Timings
Monday : 11 AM - 12 PM
Tuesday : 8 AM - 10 AM
Class Location
NR 122, Nalanda Classroom Complex
Instructor Information
Animesh Mukherjee
Professor
Department of Computer Science and Engineering
Indian Institute of Technology, Kharagpur
Phone: +91-3222283472 (Office)
+91-3222283473 (Residence)
Email: animeshm@cse.iitkgp.ac.in
Teaching Assistants
Course Evaluation
70% Tests
30% Assignments (coding in Python, Jupyter Notebooks, etc.)
[Assignments would be for individuals (not groups) which will be followed by a short Q&A session]
References
Daniel Jurafsky and James H. Martin. 2021. Speech and Language Processing. 3rd Edition (draft)
Christopher D. Manning and Hinrich Schütze. 1999. Foundations of Statistical Natural Language Processing. MIT Press
Yoav Goldberg. A Primer on Neural Network Models for Natural Language Processing Online