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Bachelor’s Programme 'Fundamental and Applied Linguistics'
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HSE Campus in Nizhny Novgorod

Bachelor’s Programme 'Fundamental and Applied Linguistics'

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Academic Supervisor
Klimova, Margarita
Manager
Чувилина Анастасия Андреевна

1B Lyvovskaya Street,
Room 145
Nizhny Novgorod 603155, Russia

Phone: +7 (831)436-74-09 * 6535

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Introduction to neural network and machine translation

2022/2023
Academic Year
ENG
Instruction in English
8
ECTS credits
Delivered at:
Department of Applied Mathematics and Informatics (Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod))
Course type:
Elective course
When:
4 year, 2, 3 module

Instructors


Malafeev, Alexey


Орлов Михаил Максимович

Course Syllabus

Full SyllabusAsk Question

Abstract

The course introduces basic concepts of neural networks, deep learning and machine translation.
Learning Objectives

Learning Objectives

  • The purpose of the ciyrse is to develop the ability to use neural network in their research and applied projects.
Expected Learning Outcomes

Expected Learning Outcomes

  • Has an idea of principles of building neural networks
  • Has an idea of the features of convolutional networks
  • Has an idea of the principles of neural networks training
  • Is able to work with Python libraries
  • Has an idea about the regularisation features
  • Has an idea of the basic principles of machine translation
Course Contents

Course Contents

  • Deep Learning
  • The Building Blocks of Neural Networks
  • Classification and Regression with Neural Networks
  • Fundamentals of Machine Learning
  • The Workflow of Machine Learning
  • The Transformer Architecture
  • Sequence-to-sequence learning
  • Modern Architectures for NLP
Assessment Elements

Assessment Elements

  • non-blocking Test
  • non-blocking Laboratory work 1
  • non-blocking Laboratory work 2
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.15 * Laboratory work 2 + 0.15 * Laboratory work 1 + 0.3 * Test + 0.4 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Kelleher, J. D. (2019). Deep Learning. Cambridge: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2234376

Recommended Additional Bibliography

  • Антонио, Д. Библиотека Keras – инструмент глубокого обучения. Реализация нейронных сетей с помощью библиотек Theano и TensorFlow / Д. Антонио, П. Суджит , перевод с английского А. А. Слинкин. — Москва : ДМК Пресс, 2018. — 294 с. — ISBN 978-5-97060-573-8. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/111438 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Authors

  • FOKINA MARGARITA ANDREEVNA
  • MALAFEEV ALEKSEY YUREVICH
HSE Campus in Nizhny Novgorod → Bachelor's programmes → Faculty of Humanities (Nizhny Novgorod) → Bachelor's Programme in Fundamental and Applied Linguistics → Courses → Introduction to neural network and machine translation, 2022/23 Academic year
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