Please make your submission before midnight!

Today is deadline for the first assignment!

We have split the first task of Word2Vec Practice to two parts. The first part is called Lite and requires significantly less effort to pass. Please have a try!

First task in the course redesigned to be easier!

The course will start on February 10. All the details are in the channel <a target="_blank" rel="noopener noreferrer" href="https://opendatascience.slack.com/archives/CUGP21CKU">#course_nlp_huawei</a>

Course start

Final Projects. NLP-course. Spring 21/22

Соревнование

Final Projects

Теория

1. Introduction to Natural Language Processing

Квест

Test 1

2. Machine Learning Basics and Text Classification

Тестирование

Test 2

3. Word Embeddings

Test 3

Practice word2vec Lite

Practice word2vec

4. Convolutional Neural Networks

Test 4

NLP course. Text classification: toxic comments

The task of to classifying toxic comments

Practice 2

5. Hidden Markov Models and Tagging

Test 5

6. Recurrent Neural Networks

Test 6

7. Topic Modeling

Test 7

8. Statistical Machine Translation

Test 8

9. Transformers

Test 9

10. Conversational AI

Test 10

11. Context-Free Grammars and Parsing

Test 11

Official support channel: <a href="https://opendatascience.slack.com/archives/CUGP21CKU" rel="noopener noreferrer" target="_blank">#course_nlp_huawei</a> in ODS.ai slack. If you are not registered, please<a href="https://ods.ai/join-community" rel="noopener noreferrer" target="_blank"> join the community</a>.

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

Logistics: 
Lectures at Thursdays 17:50 MSK online.

Seminars will be added in the meantime.

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: 
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 semester are available <a href="https://github.com/huawei-university/nlp-course-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.

leaderboard-nlp

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