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Voltar para Processamento da Linguagem Natural

Comentários e feedback de alunos de Processamento da Linguagem Natural da instituição Universidade HSE

762 classificações
194 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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126 — 150 de 194 Avaliações para o Processamento da Linguagem Natural

por CL G

17 de Jun de 2019

Fascinating and fun.

por Cindy P

5 de Dez de 2018


por 张芃捷

19 de Fev de 2020

So good progress!

por Yu Q

5 de Mai de 2019

Very good course!

por 芦昌灏

5 de Dez de 2018

wonderful course!

por Narjes K

7 de Nov de 2018

Very good course,

por Rik K

1 de Mai de 2018

Enjoyed it a lot!

por Vignesh V

2 de Mar de 2018

Excellent Course.

por boulealam c

27 de Set de 2020

this is great !!

por Bharanidharan S

2 de Jan de 2020

Excellent course

por Lucas B M

13 de Mar de 2019

Very good course

por Patrick H

6 de Abr de 2018

Awesome course.

por Arif R

8 de Set de 2020

Excellent !!!

por Alek R

17 de Nov de 2018

great course!

por Max P Z

28 de Mar de 2018

Great course!

por Laura C

31 de Mar de 2020

Good job!

por haiya1994

9 de Out de 2018

very good

por 过群

7 de Mar de 2018


por Rifat R

13 de Mai de 2020


por Владимир В

25 de Fev de 2019


por Krishna H

21 de Ago de 2020


por Joe W

9 de Jan de 2020

Amazing course!! This course introduces both classical and deep learning approaches in NLP and discusses the connection between the two. The homework is generally very well designed. The final project requires deployment in production which is a nice experience to have for real world application even though I was hoping for more in-depth model building based on the materials in the tutorials (perhaps this is covered in the honors project). One recommendation is to update the materials to include BERT, ELMO and transformers from the last two years. I know it is difficult to stay up-to-date given how fast the NLP field develops. However, this course provided enough background knowledge to learn those new topics on our own. All in all, very enjoyable learning experience and I am already applying some of the skills in my day job. Thanks so much!!

por Ivan S F

15 de Mar de 2020

The course is good. The course is worth taking. However, it is way too dense. There are very complicated concepts explained in too little time with too little context. I would suggest to break down the course into 3-4 courses within a specialization providing more examples, more context, more exercises to fully understand the material.

The final project is a nightmare where multiple different parts (amazon web services, tmux, docker, etc.) have to work all together. Not unexpectedly, a full range of errors, problems, and roadblocks arise when all these different parts have to work together for the project to work.

I finished the course including the final project and I am happy I took this course. However, the final project should have been better thought out before releasing it.

Thank you Anna and all the teaching staff for the course.

por Lefteris L

22 de Set de 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.

por Зубачев Д С

2 de Out de 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.