Application of neural networks in computational linguistics

The goal of the course is to provide a systematic understanding of neural network algorithms used in computational linguistics and to develop practical skills in applying neural networks to automatic text data processing tasks.

The course will begin with a review of “pre‑neural” algorithms, after which we will move on to artificial neural networks. Students will learn to work with the PyTorch library, gain an understanding of recurrent neural network architectures, and learn how to use them for automatic text processing. Additionally, participants in the special course will master the principle of the attention mechanism, become familiar with the Transformer architecture, and explore language models based on it.

Basic knowledge of Python programming is required to attend the course. Familiarity with courses in linear algebra and mathematical analysis is also recommended.

Classes are held at the Department of Theoretical and Applied Linguistics, Faculty of Philology, Lomonosov Moscow State University

The course program includes 18 sessions: 7 lectures, 7 seminars, and 4 practical sessions

Занятия проводятся на кафедре теоретической и прикладной лингвистики, Филологический факультет МГУ им. М. В. Ломоносова

В программе курса 18 занятий: 7 лекций, 7 семинаров и 4 практикума

Старт курса: 17 февраля 2023

Занятия будут проходить по пятницам с 9:00 до 10:30

Форма записи на курс

Набор на курс 2023 года закрыт