Oct 03, 2019
Great course! The notebooks are a perfect level of difficulty for someone learning RL for the first time. Thanks Martha and Adam for all your work on this!! Great content!!
Nov 23, 2019
Good balance of theory and programming assignments. I really like the weekly bonus videos with professors and developers. Recommend to everyone.
創建者 Mark J
•Sep 23, 2019
In my opinion, this course strikes a comfortable balance between theory and practice. It is, essentially, a walk-through of the textbook by Sutton and Barto entitled, appropriately enough, 'Reinforcement Learning'. Sutton's appearances in some of the videos are an added treat.
創建者 David R
•Dec 10, 2019
Course is not easy, videos presentation is a bit dull - but the material is cool and interesting, and the additional quizzes, videos and especially notebooks make it a great course - you learn a lot and see progress. Highly recommended.
創建者 Shashidhara K
•Dec 12, 2019
This course required more work than the 1st in the series, (may be i took it lightly as the first was not that difficult). Request : Please include some worked examples (calculations) or include in graded/ungraded quiz, will be nice.
創建者 Ashish S
•Sep 16, 2019
A good course with proper Mathematical insights
創建者 David P
•Nov 03, 2019
Really a wonderful course! Very professional and high level.
創建者 Umut Z
•Nov 23, 2019
Good balance of theory and programming assignments. I really like the weekly bonus videos with professors and developers. Recommend to everyone.
創建者 AhmadrezaSheibanirad
•Nov 10, 2019
This course doesn't cover all concept of Sutton book. like n-step TD (chapter7) or some Planning and Learning with Tabular Methods (8-5, 8-6, 8-7, 8-8, 8-9, 8-10, 8-11), but what they teach you and cover are so practical, complete and clear.
創建者 Pachi C
•Dec 08, 2019
Great and fantastic course!!!
創建者 Antonio P
•Dec 13, 2019
Great Course
創建者 Max C
•Oct 24, 2019
Some of the programming homeworks were difficult to debug due to the feedback from autograder being unhelpful.
創建者 David C
•Oct 10, 2019
A very good course. The lectures are brief and provide a quick overview of the topics. The quizzes require more in-depth reading to pass (covering material not discussed in the lectures) and the projects are difficult but rewarding and really help to cement the information. My only suggestion would be to lengthen the lectures to provide more discussion on the topics.
創建者 Marius L
•Sep 20, 2019
Overall, I found the course well made, inspiring and balanced. The videos really helped me to understand the rather austere textbook. I give 4 stars because some of the coding exercises felt more like work in progress, without the help of other students I would not have been able to overcome these issues.
創建者 Scott L
•Sep 26, 2019
This course series is an incredible introduction to the basics of reinforcement learning, full stop. The course ... style, if you will, is a bit weird at first, but it seems to have been done on purpose with the aim of making the course somewhat timeless; they are presenting maths that will not change, in a format that will (hilariously) be no more slightly corny and weird in 2030 as it is in 2019.
創建者 JDH
•Sep 23, 2019
Rating 4.3 stars – so far (first two classes combined)
Lectures: 4.0stars
Quizes: 4.0stars
Programming assignments: 4.5stars
Book (Sutton and Barto): 4.5stars
In the spectrum from the theoretical to practical where you have, very roughly,...
(1) “Why”: Why you are doing what you are doing
(2) “What”: What you are doing
(3) “How”: How to implement it (eg programming)…
...this is a “what-how” class.
To cover the “why-what” I strongly recommend augmenting this class with David Silver’s lectures (on Youtube) and notes from a class he gave at UCL. This covers more of the theory/math behind RL but covers less on the coding. Combined together with this class it probably comprises the best RL education you can get *anywhere*, creating a 5-star combo.
http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
創建者 Yicong H
•Dec 05, 2019
Jump for here to there, it's nice to have all these algorithms. My gut tells me something is not correct. Too much focus on experience, which means a lot of data. The model part is touched very little, and main focus is on when model is wrong.....
創建者 Navid H
•Oct 16, 2019
definitely interesting subjects, but I do not like the teaching method. Very mechanic and dull, with not enough connection to the real world
創建者 Neil S
•Sep 12, 2019
This is THE course to go with Sutton & Barto's Reinforcement Learning: An Introduction.
It's great to be able to repeat the examples from the book and end up writing code that outputs the same diagrams for e.g. Dyna-Q comparisons for planning. The notebooks strike a good balance between hand-holding for new topics and letting you make your own msitakes and learn from them.
I would rate five stars, but decided to drop one for now as there are still some glitches in the coding of Notebook assignments, requiring work-arounds communicated in the course forums. I hope these will be worked on and the course materials polished to perfection in future.
創建者 Chan Y F
•Nov 04, 2019
The video content is not elaborated enough, need to read the book and search on the web to understand the idea