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Kursteilnehmer-Bewertung und -Feedback für Fundamentals of Reinforcement Learning von University of Alberta

176 Bewertungen
53 Bewertungen

Über den Kurs

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....



Sep 07, 2019

Concepts are bit hard, but it is nice if you undersand it well, espically the bellman and dynamic programming.\n\nSometimes, visualizing the problem is hard, so need to thoroghly get prepared.


Aug 04, 2019

The ideal course to go with the book Reinforcement Learning: An Introduction. The quizzes and coding workshops are pitched just right in my opinion, neither too easy nor too hard.

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26 - 50 von 55 Bewertungen für Fundamentals of Reinforcement Learning

von Naveen M N S

Sep 09, 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!

von Mert İ

Aug 19, 2019

The concepts are explained in a very simple manner. Reading book then watching videos helps a lot to understand the essential ideas.

von Hennie d H

Sep 10, 2019

Really nice and clear course, love it :)

von Ignacio O

Aug 23, 2019

Excellent beginners course of a very interesting topic!

von Daniel D V

Aug 24, 2019

Very well explained, with amazing examples. Thanks!

von Justin S

Aug 23, 2019

Excellent Course! The level of difficulty is perfect. It is difficult but not impossible if you do the readings in the textbook and understand the lectures. I strongly suggest reading the book before watching the lectures. This helped my understanding significantly. The material and assignments are very interesting and informative.

Highly recommend this course to anyone interested in RL.

von Andrew D G

Aug 24, 2019

A really excellent course!

von Sriram R

Aug 24, 2019

Well organized course. Good pedagogy. Well done!

von Peter L

Aug 24, 2019

This is a nice course. I think for people with no background in RL the pace might be a little fast. A few more examples could help them understanding the concepts more easily.

von Zhonghua Q

Sep 14, 2019

The course is well designed. It contains the essential material of RL and relates closely with the RL Bible textbook. And the programming assignment is also benifical to understanding the basics.

von Sachin U

Sep 14, 2019

Great course.

von Shengjian C

Sep 01, 2019

This is a very helpful courses to help me walk through the Reinforcement Learning book with different kind of practices. Looking forward to taking course2!

von Ivan S F

Aug 31, 2019

Very practical and learning-oriented. Providing the textbook in PDF is a big plus. I think there should be more programming exercises. Great course anyway. Worth taking it.

von Stewart A

Aug 31, 2019

Great course from the home of RL

von Saraj s

Aug 29, 2019

This is the best RL course I have ever attended. Even before starting this course I had brought the textbook (the one which course instructors also recommend) and was through the first 4 chapters. I understood most of the material but when I attended the class, everything was crystal clear. I hope instructors follow up and create the remaining courses as well. Please increase prgramming assignments in number as well. Thumbs up. Thanks for this course, very grateful.

von Trevor M

Aug 28, 2019

Excellent material paired with excellent instruction.

von Иванов К С

Aug 29, 2019

It's difficult to estimate this course because it's based on the book. I mean, 90% of materials i've seen on videos were on the book. That's very unusual, but effective. However, i've learned necessary information and python tasks were useful and interesting. I'll take the next course and will see.

von Damian K

Sep 01, 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.

von Abubakr B

Sep 03, 2019

Very engaging and informative

von Christian S

Sep 02, 2019

great course; well explained and exercises reinforce the learnt material. also, great that this course uses Sutton's and Barto's book on reinforcement learning.

von Kaustubh S

Sep 02, 2019

All the concepts were well explained and this course was perhaps the best I have found for RL.

Great efforts have been put into making the course and It goes well in line with the suggested textbook.

von Ankith M

Sep 07, 2019

Builds a good foundation of basic concepts of RL.

von Akash B

Sep 07, 2019

Concepts are bit hard, but it is nice if you undersand it well, espically the bellman and dynamic programming.

Sometimes, visualizing the problem is hard, so need to thoroghly get prepared.

von Marius L

Sep 05, 2019

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

von Aditya J

Sep 16, 2019

Impressed by the knowledge of professors in the video and inspite of that they took so much interest in teaching minor concepts to students which are trivial to them.