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Natural Language Processing course (stream 5, autumn 2023)

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Final Projects. NLP-course. Autumn 2023

Хакатон

Final Projects

Теория

1. Introduction to Natural Language Processing

Квест

Test 1

Course block deadline expired on 28.09.2023 20:59

Block deadline expired

2. Machine Learning Basics and Text Classification

Test 2

Course block deadline expired on 05.10.2023 20:59

3. Word Embeddings

Test 3

Course block deadline expired on 12.10.2023 20:59

Practice word2vec Lite

Course block deadline expired on 19.10.2023 20:59

Practice Word2Vec Hard

4. Convolutional Neural Networks

Test 4

Practical Assignment 2: Text multiclass classification: store's review rating

Your task is to classify the store's review rating into 5 classes. The metric is F1-score.

Соревнование

Practice 2

Course block deadline expired on 12.11.2023 20:59

5. Hidden Markov Models and Tagging

Test 5

Course block deadline expired on 26.10.2023 20:59

6. Recurrent Neural Networks

Test 6

Course block deadline expired on 02.11.2023 20:59

7. Topic Modeling

Test 7

Course block deadline expired on 09.11.2023 20:59

8. Statistical Machine Translation

Test 8

Course block deadline expired on 16.11.2023 20:59

9. Transformers

Test 9

Course block deadline expired on 23.11.2023 20:59

10. Conversational AI

Test 10

Course block deadline expired on 30.11.2023 20:59

11. Context-Free Grammars and Parsing

Test 11

Course block deadline expired on 28.12.2023 20:59

Official support channel: <a href="https://t.me/+RxMrIGZ213lkNGJi" rel="noopener noreferrer" target="_blank">https://t.me/+RxMrIGZ213lkNGJi</a>&nbsp;

Lecturers: 
Valentin Malykh (<a href="http://val.maly.hk/" rel="noopener noreferrer" target="_blank">personal page</a>)

Logistics:Lectures at Thursdays&nbsp;19:40&nbsp;MSK online. First lecture will be at 14th of September.

Info regarding the seminars will be added in the meantime.

&nbsp;

Syllabus:

<ul>
<li>Introduction to Natural Language Processing</li>
<li>Machine Learning Basics and Text Classification</li>
<li>Word Embeddings
<ul>
<li>1st Assignment</li>
</ul>
</li>
<li>Convolutional Neural Networks
<ul>
<li>2nd Assignment</li>
</ul>
</li>
<li>Hidden Markov Models and Tagging</li>
<li>Recurrent Neural Networks</li>
<li>Topic Modeling</li>
<li>Statistical Machine Translation</li>
<li>Transformers</li>
<li>Conversational AI</li>
<li>...additional topics</li>
</ul>

&nbsp;

Prerequisites:

<ul>
<li>Basic Python Programming</li>
<li>College Calculus, Linear Algebra</li>
<li>Basic Probability and Statistics</li>
<li>Foundations of Machine Learning</li>
</ul>

Assignments:

&nbsp; There will be two assignments on the course.

Projects: 
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 runs are available<a href="https://ods.ai/projects" rel="noopener noreferrer" target="_blank"> here</a>.

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.

Лидерборд

Встреча студентов курса пройдет 22 декабря в московском офисе МТС ИИ

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Проекты

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