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Вернуться к Fundamentals of Reinforcement Learning

Отзывы учащихся о курсе Fundamentals of Reinforcement Learning от партнера Альбертский университет

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Оценки: 2,362
Рецензии: 559

О курсе

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....

Лучшие рецензии

AT

6 июля 2020 г.

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 апр. 2020 г.

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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176–200 из 564 отзывов о курсе Fundamentals of Reinforcement Learning

автор: dmin d

19 мар. 2021 г.

Very good. Has a great book suppliment to better understand the concept. The lecture and the book is highly related. So it's much easier to study.

автор: 刘旻星

1 июля 2020 г.

Getting through this course, i know about Reinforcement learning more systematically. And a solid foundamental knowledge is a beginning of success

автор: Li L

11 авг. 2020 г.

Awesome course! The concepts and basic ideas are made very clear through the videos and assignments. The programming assignments are also useful.

автор: Tristan L

15 окт. 2021 г.

Well-organized and well-executed! This course did an excellent job at introducing RL concepts and showing how they can be implemented in Python

автор: Guruprasad

9 июля 2021 г.

Assignments were the really useful to master the theoretical concepts. Instructors are really doing a good job in keeping the content crisp.

автор: vishal s

13 авг. 2020 г.

Nice course for people who are beginning Reinforcement Learning ,as the course takes you slow and steady by strengthning your basic concepts

автор: Rudi C

31 мая 2020 г.

A great introduction to the field of RL. The referenced textbook is amazing and the implementation of the algorithms is fun and instructive!

автор: Braghadeesh L

31 июля 2019 г.

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

автор: Dhar R

23 окт. 2020 г.

Excellent course. The concepts are quite abstract, so I expect to revisit them a few times again. Otherwise, it could all evaporate. Lol!

автор: Shashikant P

29 дек. 2020 г.

Excellent introduction to Reinforcement Learning. The examples used to make students understand the various concepts were truly amazing.

автор: Lukas S

23 дек. 2019 г.

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

автор: laxmikanta s

30 дек. 2020 г.

Great Content, Superb explanation with solid examples. Quiz and Assignment are really helpful to improve understanding on the topic.

автор: KSHITIJ B

22 мая 2020 г.

The basics are really introduced in a manner that one can easily build upon after reading the readings provided , enjoyed the course

автор: Animesh

15 февр. 2020 г.

I found this course very interesting. The basic concepts are explained very nicely. This course is great when a RL-noob like me : D

автор: Mert I

19 авг. 2019 г.

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

автор: Cesar A G

13 июля 2020 г.

Well structured and thought examples that expand the information on the textbook. The programming assignments are very well built.

автор: Suresh

21 сент. 2020 г.

Awesome introduction to Reinforcement Learning. The explanations are very precise and the complex concepts were easy to follow

автор: DEVANSHU S

8 сент. 2020 г.

Beautifully explains concepts in an intuitive fashion, although the addition of proofs of convergence would have been great :)

автор: Nikhil G

25 нояб. 2019 г.

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

автор: Arvin N

9 мая 2020 г.

This course was great, but I think it is not complete. I have to pass the other courses in this specialization for sure.

автор: Allyson D d L

22 апр. 2022 г.

The course is very good! Basic but because it's only the beginning of the specialization. I am exciting to complete it.

автор: Evrim A

16 нояб. 2020 г.

The course content is superb. As a suggestion, some coding and problem-solving content (as videos) would be outstanding

автор: Dylan R

22 февр. 2020 г.

Great course, reading the textbook was difficult at times, but the professors really helped me in understanding it all!

автор: Mohamed R M F

23 июня 2021 г.

it's my first time learn what is reinforcement learning and this course really helped me to get the fundamentals of it

автор: Chamakoora S R

14 июля 2020 г.

Not only this course was conceptually sound, it had inspirational sessions with researches who made big breakthroughs.