Chevron Left
返回到 自然语言处理

学生对 国立高等经济大学 提供的 自然语言处理 的评价和反馈

499 个评分
115 个审阅


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. Do you have technical problems? Write to us:



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!


Jan 02, 2019

I like this course very much. It is a good introduction for NLP. But if you want to know more about the NLP, you need to search and read a lot of posts during the learning process.


101 - 自然语言处理 的 114 个评论(共 114 个)

创建者 Ankit G

Nov 18, 2018

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

创建者 Ajeet S

Apr 19, 2019

The course is very nice. I wish there were some more examples in slides to understand the working of algorithms. Maybe its advance that's why I felt it.

If notes of every week were available then it would have been very beneficial.

创建者 Hampus L

Jun 06, 2019

The course was great. Perhaps it'd be nice to combine the lower level with some higher level Deep Learning framework at the end. Thanks!

创建者 Mark Z

Jun 11, 2019

Overall great intro to NLP. Basic techniques like word embeddings and attention are explained quite well. However, some topics are not really easy to remember from this course, such as Topic modeling using LDA (which I understood much deeper during Bayesian Methods for Machine Learning course from the same specialization).

创建者 Neel K

Sep 17, 2019

Course is well organized. Just some problems are related to assignments, There no exact guided steps for assignments and quiz. Lectures are more concerend about theory and less about pragmatic problems. Please make discussion forums active and more connected. Course does not have option to send message to anyone personally take help and advice which is something unrealistic.

创建者 Lefteris L

Sep 22, 2019

This course offers a really good intro to all of the state of the art techniques used in NLP. Its course is structured by heavy impact papers from the literature and the instructors do a really good job in explaining.

The quizzes are good and help you understand the material.

If there is one thing I didn't like in this course, it was the programming assignments. Their structure was really big and aimed really long. Thus, I often felt that I didn't know what I was doing and for what reason. The assignments from Andrew Ng's Deep Learning's Specialization "Sequence Models" course were far better and helped me gain much intuition on how to code real tasks.

创建者 Зубачев Д С

Oct 02, 2019

It was a good course. All in one breath. I would like to have more practical tasks in which you need to write more code yourself, and not just fill in the missing cells. Of course, I am very grateful to Anna and Andrey for their work. Separately, we would like to note the penultimate task-the final project. It is complex and interesting. I believe that it would be correct to use the computing power of Azure instead of AWS.

创建者 刘禹杰

Oct 13, 2019

The quality of this course is good, but I still feel that the algorithm introduced is basic. It is better to combine the leading edge algorithms. Actually, I finished it very early, but I stuck in the fifth week of the dialogue robot job for a long time. I feel that this part of the time is not very worthwhile, because time is spent on the more cumbersome model deployment instead of focusing on Algorithm optimization, of course, model deployment is also very important, this is also a test for me, so I give 4 stars.

创建者 Angela B

Jul 06, 2019

Good information, but I am struggling understanding the presenter. The course feels a bit forced.

创建者 Luke B

Jun 03, 2019

This was a good class, and I want to give it more stars, but the default path for completing the final project requires far more time than the course specifies, making it difficult to properly manage one's time.

创建者 ravi k

Aug 07, 2019

Good and useful content but weak quality in providing directions in assignments and zero help

创建者 Omar F

Sep 02, 2019

The course material overall is good. However, the assignments are not very beneficial from my point of view.

The peer review is totally a mess -no one really review an assignment-

创建者 Joris D

Sep 22, 2019

This is a very good course, brought with clarity and humour, and excellent quizzes and assignments to assess your understanding of the material. The big problem it has is the final project, which requires you to run a piece of software on an AWS free tier server. An impossibility, because the software requires more memory than Amazon offers in its free tier. Moreover, as it crashes every few hours, peer reviewers can find it not working and have to contact you to restart it. Constant monitoring for several days is required.

创建者 Ignacio G B

Jun 07, 2019

Shallow theoretical explanations (just mentions and references). Disconnected assignments from theory.