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Вернуться к Practical Reinforcement Learning

Отзывы учащихся о курсе Practical Reinforcement Learning от партнера Национальный исследовательский университет "Высшая школа экономики"

4.2
звезд
Оценки: 359
Рецензии: 103

О курсе

Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. --- with math & batteries included - using deep neural networks for RL tasks --- also known as "the hype train" - state of the art RL algorithms --- and how to apply duct tape to them for practical problems. - and, of course, teaching your neural network to play games --- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits. Jump in. It's gonna be fun! Do you have technical problems? Write to us: coursera@hse.ru...

Лучшие рецензии

AK

May 28, 2019

This is one of the Best Course available on Reinforcement Learning. I have gone through various study material but the depth and practical knowledge given in the course is awesome.

FZ

Feb 14, 2019

A great course with very practical assignments to help you learn how to implement RL algorithms. But it also has some stupid quiz questions which makes you feel confusing.

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76–100 из 103 отзывов о курсе Practical Reinforcement Learning

автор: Roland R

Apr 15, 2020

Topic is very interesting and most of the content is presented in an understandable way. A lot of additional material is presented that helps to deepen your knowledge. The programming assignments also help a lot to grasp what really is going on. Some of the notebooks are a little bit broken (missing RL environments, broken submit scripts, some tasks not clear, ...). But all in all very good.

автор: Guy K

Nov 04, 2018

great content !

administration could benefit from some improvements (some exercises required "hacking" but the course forum were helpful)

Also, would be great if the slides can be shared.

this is the 2nd course I take from HSE. very happy with the content and the level. exercises are excellent !

I will happily continue to the next course in this specialization :)

автор: Jonas B

Jun 10, 2018

Content provides a good - and useful :) - overview of reinforcement learning. The hands-on exercises in the notebooks were the main reason I decided to do the course, and I enjoyed doing them. However, they did contain a lot of errors and broken code,. This would need to be fixed for the course to earn a 5/5.

автор: Sean H

Jul 29, 2019

Overall very informative and well done course, I highly recommend it. The support in the discussion forums is the main area where it lacks. Sometimes the topics are hard to grasp, so it's really a big help when there is good support in the forums.

автор: Chun T Y

Jul 11, 2019

Some details are not explained as clear as it can be, maybe there can more reading material to bridge the knowledge gap between course syllabus and intermediate level ML experience. Nice work tho!

автор: Francesco R

Jul 03, 2018

Wonderful content and super interesting problem assignments, but please fix the bugs in the graders and spend some time to adapt the code to the Coursera platform.

автор: Roman P

Feb 05, 2019

Four stars only because the notebooks/excercises don't work well. Aside of that, I learned a lot in this class. Thank you!!

автор: 林佳佑

Jan 26, 2019

this course is helpful to learning Reinforce learning, but with some ambiguous context need a lot time to understand,

автор: Mark C

Jul 23, 2018

Great instructors and course material, but there are enough bugs in the quizzes and assignments to be annoying.

автор: Shahram N S

Feb 11, 2019

Overall a good course, But there are many bugs and errors in the programming portion of the course.

автор: Matthieu G

Sep 18, 2019

+ Great coding assignments : practical and motivating !

- Sometimes the videos could be more clear

автор: Maxim V

Apr 02, 2020

Awesome course, although some quizzes and programming assignments could be more user friendly.

автор: Emilio P

Aug 11, 2019

Wonderful course. Just would need a little bit more work on the subtitles.

автор: Потапчук А А

Jun 30, 2018

It still a beta:(

автор: Philippe M

May 11, 2020

Notebooks are very useful to learn the theory and I certainly learned a lot throughout this course. However, codes in homework often lack of clarity and sometime includes errors and not enough assert checks. The audio is also hard to and understand, the slides are often poor, missing keywords, recaps, organization, sometimes you have 4 dense slides per lessons. Would be great to have better slides as a support of the speech. The questions during videos are really useful. The teaching staff is really reactive and many issues, difficulties have already been solved by the community, which helps a lot for autonomy. So thank you, it was really really useful, but it could have been better and cleaner !

автор: Kristoffer M

Sep 10, 2018

The teachings are actually quite good, and the problem sets are fine, but there are so many bugs in the submission methods that you spend halv of your coding time trying to debug the submit methods. Frustrating. If they fix the course, this course will be highly recommended.

автор: Xiaoahe X

Feb 20, 2019

The course is well organized. Reference and extra learning items is helpful to enhance the knowledge.

BUT! There are so many small bugs in the assignments that it really takes time to fix and make the course hard to get passed.

автор: Helmut G

Aug 22, 2018

Sometimes it is hard to understand/follow the instructors. And the assignments (especially the grader) are bit too much beta, which causes a lot of extra effort.

автор: Felix A

Mar 18, 2019

The course itself is great, but the assignments are a bit chaotic (so make sure to bring a lot of patience and willingness to bugfix)

автор: Ishan

Jul 09, 2020

Lectures are mathematical and theoretical.

Assignments are practical. NO EXPLANATION OF WHAT ASSIGNMENTS IN CLASS

автор: Dai T

Jul 29, 2018

Lots of theory and definition should be illustrate in detail on ppt.

автор: Sylvain D

Dec 03, 2019

Good

автор: Lars J I

May 14, 2020

The reading material was very weak and scattered. Some of the blog posts were nice but in general it's not very helpful to link a bunch of publications and a couple full-length books. Instead, It would be nice to have a small document that goes through the material in written form (if even just a summary).

The assignments were not very good and lacked depth. Often times I found myself implementing some formula/algorithm without knowing how it works or why. As such, it was easy to finish the assignments without learning anything. I would rather have two in-depth assignment (maybe an implementation from scratch with guidelines) than 6 or 7 shallow ones. The problem with the shallow ones is that there's no incentive to take the time and understand the functions that are already pre-coded. This makes it hard to follow whats going on "under the hood". You can, of course, still take the time to do this, but I feel like a true understanding of everything that goes on in all the algorithms in all the assignments would take far too long.

There was a general lack of theoretical material regarding the covered methods and algorithms. Why do they work?

автор: Anders A

Jun 13, 2018

The collection of curriculum was great together with links to external resources. However, there was several weaknesses with the course. First, several of the assignments had problems with submitting the code, which required some extra coding to be able to submit assignment. Event with multiple weeks with many students reporting the problem, nothing was corrected. Second, the lectures were weak. I knew something about Q-learning from before, but after the lecture I was more confused than when I started. The topics I were not familiar from before the course,I ended up searching online or using the resources linked to instead of the lectures. The question exercises felt arbitrary and not helpful at all. The programming exercises were not well explained. I were able to finish them, but to much unnecessary annoyance.

автор: Maxim B

Jul 26, 2018

Don't let Alexander Panin read lectures. He is an awful speaker: always in a hurry, uses so many redundant words in his speech. He "killed" so much interesting material in this course. I truly believe he could write cool lecture notes and handouts (currently the course lacks it). Alexander, please, write materials, don't read lectures.