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Voltar para Processamento da Linguagem Natural

Comentários e feedback de alunos de Processamento da Linguagem Natural da instituição National Research University Higher School of Economics

747 classificações
192 avaliações

Sobre o curso

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:

Melhores avaliações

2 de Ago de 2020

It's a comprehensive course on NLP. The instructors clearly explain both the traditional/classical approaches and modern approaches such as neural networks in NLP.

17 de Dez de 2019

One of the best courses I took from coursera. Good mathematical knowledge, resources provided are related to current research. Assignments are more than expected.

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151 — 175 de 192 Avaliações para o Processamento da Linguagem Natural

por Neel K

17 de Set de 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.

por Joana N R

26 de Ago de 2020

Very complete course. Wish the instructors would provide more support and answer our questions in the discussion forums. The exercises seemed a bit complex in comparison to the lessons. Overall, great theoretical course. Loved the lessons, the practical quizzes and programming exercise not so much. Definitely recommend if you want to get familiar with NLP techniques.

por Игнатовская В А

6 de Dez de 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!!!!

por Fernaldy A F

29 de Ago de 2018

Great course but not easy one.. You must have required knowledge..

You need extra effort to finish quizzes or assignments, and also search in forum discussion or internet..

I think, the lectures are too theoretical, but that's good if you are curious or researchers that need to know about state of the art related NLP..

Overall this is worthy to take..

por Vivek G

25 de Ago de 2020

The course seems tough when you think just to learn from the slides, but in actual you need to learn a lot from the papers published for that topic. Overall the course was tough if you directly come to this 6th course of Machine Learning specialisation. The course tutor were very good, and explained with the best possible examples.

por Mark Z

11 de Jun de 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).

por João B P M J

8 de Dez de 2019

I think the provided material needs to be updated. Specially the material concerning TensorFlow. Many subjects and assignments let us wondering too much because it because there is a mismatch between the theoretical and the practical, and because the TensorFlow isn't updated it was hard to find additional help online.

por Zhaoqing X

24 de Jul de 2018

It's a very nice course! It involves so many aspects in NLP, and the assignments are especially valuable. The only thing I'm not satisfied is that it lacks enough help from the material and the forum when I got a bug from my assignments or confused by the instruction.

por Akash S

22 de Mai de 2018

Very good course!! A big thanks to all the instructors. However I feel the course covered a lot of stuff which affected its focus. May be it would have been better to focus on fewer techniques but in greater detail both in theory and assignments.

por Helmut G

10 de Jul de 2018

Nice course. However, trying to pass the assignments can sometimes feel like a nightmare, because there is no feedback from the grader that would lead you into the right direction. Luckily you can get useful information in the discussion forum.

por Mika R

19 de Nov de 2019

I would recommend the mention of the library version in each given code to avoid the wrong use of the arguments and even attributes. For instance tf 2.0 do not have contrib and yet in certain part of the code, we are "required" to use that.

por Putcha L N R

24 de Dez de 2018

Anna and group is great at teaching. However, a lot of graded assignments were a lot ambiguous with many important details missing. It would be a lot more helpful, if the content needed for assignment is explicitly mentioned! Thank you!

por Ajeet s

19 de Abr de 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.

por Armughan S

19 de Mai de 2020

The course had an advanced content and was taught at a good pace. Though there are some concepts which were not elaborated and needed to be understood from different sources.

por Ahammed J

24 de Abr de 2020

This is basic to advanced level course. you should have significant amount of knowledge in the field, if not you have to do additional research .Over all good course.

por Santoshi29 K

21 de Mar de 2019

explanation on Fundamentals are good.. it would be better if models and methods are explained by applying them to some real time examples.

por Hampus L

6 de Jun de 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!

por Raúl A C G

28 de Dez de 2020

Really nice course, you might want to add some more tips in the programming assignments but beside that really awesome content

por Ruperto P B C

3 de Abr de 2020

It is a very good course. My only request is related to update the tasks along the course to use Tensorflow 2.0

por Archana C

23 de Jun de 2020

More detailed explaination for week 5 project required. a video can be released for AWS use.

por Francisco R

21 de Ago de 2018

Time estimated for assignments is well below the actual time taken to complete them.

por Johannes J

14 de Jan de 2019

I learned a lot. The tasks are challenging, but somehow manageable. Thanks!

por Ahmad A

30 de Jul de 2020

More detailed slides and longer elaborating of ideas can be an advantage

por Ankit G

18 de Nov de 2018

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

por Daksh M

6 de Abr de 2019

It has less content on abstractive summarization.