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Practical Reinforcement Learning, Национальный исследовательский университет "Высшая школа экономики"

4.1
Оценки: 183
Рецензии: 51

Об этом 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!...

Лучшие рецензии

автор: 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.

автор: VO

Mar 17, 2019

Well Prepared and taught course.. Will highly recommend as the primer for reinforcement learning

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Рецензии: 51

автор: MASSON

Apr 07, 2019

Interesting topic, however several things are not acceptable for a paid course:

+ Some assignments are a mess, it's crazy hard to get the environments working right, very little instructions and explanations

+ Assignment graders are broken and require you to fix them manually

+ No consistency between the notations of the different lecturers

+ Slides from videos are not provided (seriously ?!)

Overall, the course does not look serious, a kind of alpha version.

автор: Felix Altenberger

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: Vaibhav Ojha

Mar 17, 2019

Well Prepared and taught course.. Will highly recommend as the primer for reinforcement learning

автор: Antony Lawler

Mar 12, 2019

Course not ready and has installation prerequisites. Seems to use a libraries (Docker, Env).

I waste too much of my time trying to install libraries and dependencies for online courses, most of which become obsolete within a year or two.

Additionally, the logic embedded within the library is often the thing I want to learn, and abstracting it only teaches me about the bugs and shortcomings of that library.

автор: Xiaoahe Xue

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: Ashish Jagadish

Feb 19, 2019

Horrible graders starting from week 3. A lot of time wasted in fixing grader issues which is course provider's primary job. This is a paid course for goodness sake. No proper communication by course's staff/mentors even in the discussion forums.

автор: Hany Abdelrahman

Feb 16, 2019

The course gives a good intro to reniforcement learning. I liked the fact the assignments here are shorter compared to other coursers. However, the quality of preparation of the material is very low. In many cases there are problems with the code and you cannot submit from coursera. I had to download the docker container locally and fix the bugs in order to submit. Quizes are not very nicely prepared and mathematical notation not very clear. I think I struggled a lot to get some of the quizes finished as the accepted score is quite high and some questions require multiple answers and you have to get them all right in order to get a score. I think the authors need to spend more time refining the quizes as well as the assignments

автор: Fan Zhou

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.

автор: Shahram Najam Syed

Feb 11, 2019

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

автор: Hamed Niakan

Feb 09, 2019

I would give it -5 star if it was possible. The course material is so vague but still understandable if you sleep on them 10 times more than watching it. Maybe Andrew Ng courses or Python Course or Advanced ML course on google cloud (GCD ) spoiled me However statistically and self-judgement , this is not the case.

The instructor talking super fast with some Russian accent that could beat any translator machine I bet. What s more, the instructor some quite of time, talking about things which are not consistent with slides and also sometimes he does not explain some formulas or modelings.

The assignments are full of grammatical errors and they are super confusing. Very simple but super confusing leads you to have the grader failed you.

But , The worst part is if you take this course you will be all on your own and no body help you out as TA . If you check the forum discussion you see how many people complaining and how many questions left with no answer. I took this course as granted , but this is my responsibility to give back my feed back to potential learners.

Note that this is my feeling from the first week of class , I hope my idea change later.