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Avis et commentaires pour d'étudiants pour Fundamentals of Reinforcement Learning par Université de l'Alberta

4.8
étoiles
2,385 évaluations

À propos du cours

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will: - Formalize problems as Markov Decision Processes - Understand basic exploration methods and the exploration/exploitation tradeoff - Understand value functions, as a general-purpose tool for optimal decision-making - Know how to implement dynamic programming as an efficient solution approach to an industrial control problem This course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL. After completing this course, you will be able to start using RL for real problems, where you have or can specify the MDP. This is the first course of the Reinforcement Learning Specialization....

Meilleurs avis

AT

6 juil. 2020

An excellent introduction to Reinforcement Learning, accompanied by a well-organized & informative handbook. I definitely recommend this course to have a strong foundation in Reinforcement Learning.

HT

7 avr. 2020

This course is one of the best I've learned so far in coursera. The explanations are clear and concise enough. It took a while for me to understand Bellman equation but when I did, it felt amazing!

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526 - 550 sur 569 Avis pour Fundamentals of Reinforcement Learning

par Nga T

27 déc. 2021

I dont understand the two games in this course. I have no idea how to mark them as done.

par Daxkumar J

3 févr. 2020

this is a basic course of the RL and its very great to learn with University Alberta.

par Simon N

20 déc. 2020

Very good introduction. Helps you get through Sutton and Barto (free pdf supplied).

par Anirudh B

13 mai 2020

Needs more coding implementation according to me. But overall theory was good.

par Zia M U D

4 mai 2020

Tutors are fantastic, but should also focus on programming not just on theory.

par Mohamed H

14 févr. 2020

I think it will be perfect if the board and pen are used to drive equations.

par Maxim V

6 janv. 2020

Good content, but most of it is in the textbook, not so much in the videos.

par Eli K

31 oct. 2021

Programming exercises teach the material a lot better than quizzes

par Sriram S

17 avr. 2020

The course was cool but needed some more programming assignments.

par Francisco R

15 juin 2020

Excellent in terms of learning the foundations of RL.

par 袁之日

29 mars 2021

There could be more coding examples for each module.

par Jeroen v H

17 oct. 2019

Quite theoretical. But a good base of the concepts.

par Husam D

4 nov. 2019

I wished there were more coding assignments

par Shahram E

25 juin 2020

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par Matin S

13 janv. 2022

it was a bit hard in code assignments

par Mark R

26 oct. 2019

Interesting course.

par Arnaud 3

10 oct. 2021

good course

par Abhishek U

21 janv. 2022

Great

par 배병선

31 oct. 2019

Good!

par Arpan M

17 oct. 2020

good

par Austin H

19 mars 2022

I found this course difficult to get through, even tedious towards the end; this is a fundamentals course after all so it being heavily theoretical was to be expected.

I found the practical assessments challenging and very good for developing the understanding of what had been taught; however one practical in the first week and one in the fourth week was too few. I was longing for the final assignment!

It remains to be seen how relevent this is to the upcoming modules (I do feel that I have a good grounding and understanding of the underlying process so maybe it was a necessary slog). I hope that they are more practical!

Very small observation: the use of bespoke Python packages with the online notebooks was also a bit frustrating. I like to be able to work off line (e.g. in Anaconda) and I also wanted to try and work out some of the challenges in R but without access to the bespoke packages it would have been too involved. I understand that you have a lot of students though and online notebooks are easier to manage.

par Youval D

21 janv. 2020

Good examples can simplify things greatly. there where several places where an extra step would add value. Some lessons, such as the problem with the trucks could go a little deeper. Assignment grading system is buggy. I spend hours (that I do not have) because I used "transition" as a variable. After I figured this out, I was no longer able to know if other error is due to some other things the Notebook does not like or if there are actual errors. I also posted some questions but never got any response to any of them.

par Chandan R S

9 mai 2020

Not much satisfied with the course structure...

To successfully understand and complete this course, you constantly need to refer the reference book.

Most of the students are referring to online courses so that they can learn more efficiently than reading,

any casual book reader can easily complete this course but for the person who like to learn from videos rather than book reading (like me), it was not so great experience.

par Rafael C P

12 mai 2020

The content is there and it is good, but teachers lack good teaching skills and lessons feel rushed (Ng lectures come to mind as positive examples of good practices). Also, lessons aren't self-contained, as you need to read the book if you want to get good grades on the tests. I was looking for a smoother experience than the book, not to be told to read the book, which I can do without a course.

par tom

16 déc. 2020

I would have learned more if the course had a coding assignment each week, or at least example code available for similar problems. I had a good theoretical understanding of everything we needed to do but very poor practical understanding.

The course did serve as a good introduction to the theory of reinforcement learning, and certainly acts as a good starting point.