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

2,499 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


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.


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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326 - 350 sur 600 Avis pour Fundamentals of Reinforcement Learning

par khuongnd6

18 juil. 2021

It is a great course to start learning reinforcement learning!

par Yong C

31 oct. 2019

It's good to learn about reinforcement learning in fundamental

par Francois L

18 nov. 2020

Excellent, it makes the book so much more easy to understand!

par Francesco M

4 août 2020

Extremely good: a stellar course for beginners in this field!

par Tanay G

19 juil. 2020

Really liked the way material was presented and learned a lot

par Michel H

13 juin 2022

Awesome Course. Follows the great Sutton Book . Recommended!

par Kunal S

10 oct. 2021

Great course. The quizzes and assignments were also perfect.

par Anubhav T

9 mai 2020

Excellent course to get introduced to Reinforcement Learning

par Max L

4 mai 2020

Awesome! Clear instruction with interesting coding example!

par Joost G

26 mars 2020

Interesting lectures and good quizzes+programming exercises.

par Marius L

5 sept. 2019

Engaging, challenging, and the math was just doable. Thanks.

par Mr. D S J D P

5 juin 2020

I struggled in programming part , but a very efficient tool

par Ruosen L

2 avr. 2020

Spent tooooooo much time on reading materials than imagine.

par Turgay P

27 juil. 2020

Great videos and an e-book to learn the fundamentals of RL

par alex x

21 mai 2020

Very good course, hope there will be more course like this

par Vincenzo C

16 févr. 2022

Fantastic course. Reinforcement AI model are fascinating

par Qasid S

27 sept. 2020

A well-organized introduction for Reinforcement Learning.

par Jicheng F

11 juil. 2020

This is the best online course I've taken ever. Good job!

par Chanon K

28 juin 2020

A great course that really focusing on fundamentals of RL

par Adarsh

16 mai 2020

very good course .

very well explained by Adam and Martha

par Pradyumna M

3 avr. 2020

Amazing course with optimum blend of theory and practice.

par Oleksandr M

6 oct. 2019

Great course! Good explanations, interesting assignments.

par Garrett S

10 août 2019

Explained in a very simple way, with helpful assignments.

par Sergio B

22 mai 2020

Outstanding explanations and assignments. Very hands-on.

par Da

30 oct. 2019

Really interesting course based on Sutton and Burto book