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Natural Language Processing, National Research University Higher School of Economics

4.7
Оценки: 236
Рецензии: 58

Об этом курсе

This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. Upon completing, you will be able to recognize NLP tasks in your day-to-day work, propose approaches, and judge what techniques are likely to work well. The final project is devoted to one of the most hot topics in today’s NLP. You will build your own conversational chat-bot that will assist with search on StackOverflow website. The project will be based on practical assignments of the course, that will give you hands-on experience with such tasks as text classification, named entities recognition, and duplicates detection. Throughout the lectures, we will aim at finding a balance between traditional and deep learning techniques in NLP and cover them in parallel. For example, we will discuss word alignment models in machine translation and see how similar it is to attention mechanism in encoder-decoder neural networks. Core techniques are not treated as black boxes. On the contrary, you will get in-depth understanding of what’s happening inside. To succeed in that, we expect your familiarity with the basics of linear algebra and probability theory, machine learning setup, and deep neural networks. Some materials are based on one-month-old papers and introduce you to the very state-of-the-art in NLP research....

Лучшие рецензии

автор: GY

Mar 24, 2018

Great thanks to this amazing course! I learned a lot on state-to-art natural language processing techniques! Really like your awesome programming assignments! See you HSE guys in next class!

автор: TL

Jul 08, 2018

Anna is a great instructor. She can explain the concept and mathematical formulas in a clear way. The design of assignment is both interesting and practical.

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Рецензии: 59

автор: Glorian Yapinus

Dec 12, 2018

Very good course with tough assignments. Expect to take more time to digest the material on the video and work on the assignments

автор: Anurag

Dec 09, 2018

Content is so good. Cheers for the makers.

автор: Игнатовская Валерия Анатольевна

Dec 06, 2018

There were basic introduction as for me, without almost any proofs and mathematical constructions. It was interesting but after this course actually I can't say that now I can do it from the beginning to end for myself, only some functions to include in existing code. Last instruction about AWS was terrible! There were too many questions about it!!!!

автор: Cindy Pe

Dec 05, 2018

お疲れ様です。ありがとうございます。

автор: 芦昌灏

Dec 05, 2018

wonderful course!

автор: Alexander Sigman

Nov 19, 2018

This is the most rigorous NLP course that I could find on Coursera or any other MOOC provider. A thorough introduction to both classical and NN models for a variety of NLP problems and tasks, drawing upon recently published articles.

The quizzes and programming exercises do at times exceed the content covered in the lectures, but if one does not mind supplementing the lecture content with self-study/problem solving, then this is not so much an issue.

The main suggestion that I would give is to reduce the numbe of peer-graded assignments (there were 3 in the span of this 5-week course). The peer grading component is time-consuming and error-prone.

автор: Ankit Gupta

Nov 18, 2018

Excellent Course on NLP. Need more focus on RNN/CNN/Sequence modelling

автор: Alexander Riley

Nov 17, 2018

great course!

автор: Melesio Crespo Sánchez

Nov 11, 2018

I really liked this course, since it has many practical examples in how to apply nlp tasks for real applications. I highly recommend this course.

автор: Narjes Karmeni

Nov 07, 2018

Very good course,