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

4.8
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2,333 évaluations
557 avis

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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101 - 125 sur 562 Avis pour Fundamentals of Reinforcement Learning

par Stefan K

4 déc. 2020

The course covers the fundamentals of reinforcement-learning and also deals with complex mathematic equations. However the math is very good explained in the videos and the 2 programming exercises help a lot for understanding this topic.

par Steven W

11 mai 2021

Solid class covering the basics of tabular Reinforcement Learning.

They follow the Sutton and Barto book pretty closely, so they start with some dummy examples to demonstrate things. The real interesting stuff isn't until a later course.

par Damian K

1 sept. 2019

Slow means smooth. Smooth means fast. This course introduces you efficiently into the world of RL. And this is what you want. Everything is perfectly to the point. All exercise are here to boost your understanding. Highly recommended.

par Vedant D

29 oct. 2020

This course provides a good fundamental knowledge about the Reinforcement Learning. The source material, RL by Sutton and Barto, provides very good intuition od concepts with examples and also explains every topic in much detail.

par MIN-CHUN W

31 mai 2020

Course contents are good and easy to understand. Textbook is really a good supplement to lecture videos. Assignment difficulties are between being easy and moderate. It's really fun and encouraging when completing the assignments.

par Naveen M N S

9 sept. 2019

The pattern of this course is amazing. Each video is short and has a specific objective that's clearly stated. This approach to teaching made tough topics look easy. Assignments and quizzes were doable. Amazing experience overall!

par Surya K

5 avr. 2020

Course was beautifully made. I tried to learn RL from multiple different courses but I couldn't understand them. This course was different however, the assignments were made in a way that helped me understand concepts concretely.

par Ola D

13 avr. 2022

E​xcellent!

V​ery good videos, very pedagogical teachers!

V​ery good book!

L​ooking forward to upcoming courses

T​his (in competition with the Data structures and algorithms specialization) is the best I have seen yet on Coursera!

par Sharath K

20 juin 2021

This is the best course I've found on RL. The lectures are to the point and both the lecturers are very good. The best part however is the graded assignments at the end of each week where we get to apply everything we learnt.

par LI C Y

2 mai 2022

This is not an easy cousre even to a computer degree graduate but it opens my eyes further on AI. I am understanding why RL is really quite different from ordinary supervised/unsupervied machine learning and neural networks.

par Nilesh A

22 févr. 2022

Challenging and perfect introduction to reinforcement learning with a great blend of theory + quizzes + practical and discussions in between to engage. Thank you everyone for this course. Moving on to the next course.

par Juan P V H

28 févr. 2021

Really good course.! The videos help to understand difficult concepts. The last assignment was challenging for me (I'm Ph.D. in electronics, not in computer science). In general a really good and recommended course.!

par Ismael E

29 mars 2021

Great course. I specifically recommend it as a completion to the reference book by R. Sutton. That course really helped me better understand some of the key concepts in the book. Looking forward to the next course.

par Andrew S

10 août 2020

Amazing course. Amazing contents. The book is perfect and the lectures help clarify doubts that one may have from reading the book. With there were more programming assignments, but still it is a very good course.

par Guto L S

27 mai 2020

Very good course! It introduces basic concepts necessary to understand the basic reinforcement learning algorithms. The course is well structured, and the practical activities help a lot to fix the studied content.

par VBz

22 oct. 2019

Short videos, with list of objectives at the beginning and recap and the end, and clear explanations in between. In my opinion, all teachers should watch these videos to get an example on how good courses are done.

par Nhu N A

30 mai 2020

The reading is a little bit challenging, but everything was explained very clearly with helpful examples in lecture videos. Absolutely recommend for someone who want to explore the field of Reinforcement Learning.

par Shahriyar R

22 sept. 2019

Extremely useful course. Especially the format is very effective. First read the book, then listen the extra explanations and write Python code. Concepts are really clear for me now. Thanks for such amazing work.

par Dani C

25 juil. 2020

I was already familiar with a lot of the subjects in the course, but the way Martha and Adam explained everything really cemented all of the knowledge for me. Now instead of just familiarity I have real skills.

par Tristan S

7 avr. 2020

Great course for learning fundamentals. My only complaint is that I don't quite feel comfortable implementing what I have learned with coding yet. Maybe as I progress in the specialization this will get better.

par Rafael B M

16 août 2020

The course build up a solid ground for building more complex concepts of Reinforcement Learning, It's essential to master the core fundamentals of RL in order to seek more powerful and sophisticated methods.

par Nicolas S

11 mars 2020

Excellent course, with an excellent explaination of Markov Decision Process and Dynamic Programming by the 2 teachers. The quizzes and the final exercice are challenging and make you search in the text book.

par Dashiell S

2 avr. 2021

Well designed, well taught course. I think I'd have liked it if there were more and tougher programming assignments as opposed to the quizzes, but this definitely provides an accessible introduction to RL.

par Jau-Jie Y

2 juil. 2021

Very good explain, and included some real world example, like trunk assign.

The dynamic animation of grid world MDP calculation also was good, though I hope more slowly show the steps interval.

Thanks a lot

par Gökhan A

22 oct. 2019

This course is very benificial for the people who want to attempt to the area of reinforcement learning. People should regularly follow the book in parallel to video lectures to benefit from this course.