Natural Language Processing (NLP) is a domain of research whose objective is to analyze and understand human languages and develop technologies to enable human machine interactions with natural languages. NLP is an interdisciplinary field involving linguistics, computer sciences and artificial intelligence. The goal of this course is to provide students with comprehensive knowledge of NLP. Students will be equiped with the principles and theories of NLP, as well as various NLP technologies, including rule-based, statistical and neural network ones. After this course, students will be able to conduct NLP research and develop state-of-the-art NLP systems.
Valentin Malykh (personal page)
The lectures are presented at 10:15 MSK each Tuesday online and seminars at 18:30 MSK each Tuesday online.
Course started: 14th of September 2021.
The main lectures end: 16th of November 2021.
There will be two assignments on the course.
The participants will be suggested to work on a project during the course. The successful project development is crucial to pass the course.
The projects from previous semester are available here.
Introduction to Natural Language Processing
Machine Learning Basics and Text Classification
Convolutional Neural Networks
Hidden Markov Models and Tagging
Recurrent Neural Networks
Context-Free Grammars and Parsing
Statistical Machine Translation
The task of to classifying toxic comments