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学生对 阿尔伯塔大学 提供的 Fundamentals of Reinforcement Learning 的评价和反馈

4.8
stars
565 个评分
144 条评论

课程概述

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....

热门审阅

PV

Nov 10, 2019

I understood all the necessary concepts of RL. I've been working on RL for some time now, but thanks to this course, now I have more basic knowledge about RL and can't wait to watch other courses

AB

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.

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51 - Fundamentals of Reinforcement Learning 的 75 个评论(共 142 个)

创建者 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.

创建者 André B

Dec 01, 2019

I really enjoyed this course. The examples and the infrastructure provided (jupyter notebooks as assingments) made this course one of the best MOOCs that I have ever taken

创建者 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.

创建者 Qianbo Y

Jan 08, 2020

A very good course integrated with Sutton and Barto textbook. A good foundation of RL can be learned from this class. It also balances well with theory and practice.

创建者 Saikat M

Aug 08, 2019

Good course following the classic book but it is kept at an easy pace for diverse people to be able to understand and apply the concepts of reinforcement learning.

创建者 Max C

Oct 24, 2019

Got me kickstarted with RL pretty well. I tried reading the RL book myself previously, but having complementary lectures and assignments made all the difference.

创建者 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.

创建者 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!

创建者 June X

Aug 06, 2019

I love their way of teaching, they ask you to read, understand firstly, and then start to give a lecture about what it is, which helps a lot to understand.

创建者 braghadeesh

Jul 31, 2019

Great course and awesome instructors. Wish this course should have been announced much earlier. Thanks for offering such a wonderful course.

创建者 Lukas S

Dec 23, 2019

Very well structured, good examples, and helpful quizzes. I think (even) more programming assignments would make the course even better.

创建者 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.

创建者 Nikhil G

Nov 25, 2019

Excellent course companion to the textbook, clarifies many of the vague topics and gives good tests to ensure understanding

创建者 AhmadrezaSheibanirad

Oct 27, 2019

This course is one of the great online course in Coursera which help people dig into reinforcement learning correctly.

创建者 Prudhvinath R

Dec 03, 2019

Everything is explained in detail. The theory behind each logistic is clearly explained by both the Professors.

创建者 Seyyed M

Sep 28, 2019

To have the best performance in the course, read the related textbook sections at the beginning of each week.

创建者 Justin S

Oct 06, 2019

Great class! Learned a lot with two really fun and enthusiastic professors. Looking forward to the next one.

创建者 Tong Z

Oct 04, 2019

Good course in coherence with the book by Sutton and Barto (2018)! Better than reading the book alone.

创建者 LIWANGZHI

Jan 05, 2020

A great introduction to RL. It provides ton of materials and makes everything clear at the same time.

创建者 Lik M C

Jan 02, 2020

It is a great course! The concepts are elaborated very clear. The materials are well prepared.

创建者 Christos P

Dec 11, 2019

Great reading material and videos. The assignments really help to better understand the theory.

创建者 Wang G

Oct 09, 2019

Very detailed explanations in the foundations of RL. Thanks both lecturers and the staffs!

创建者 John H

Sep 18, 2019

Very good, I suggest reading the text closely and doing exercises to get the most benefit.

创建者 Anubhab G

Jan 09, 2020

A solid foundation for RL and great pedagogical explanations!!! Highly recommended!!

创建者 Xunzhao Y

Nov 07, 2019

The class is quite well organized. Instruction is clear and textbook is excellent.