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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: 2,385

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!

Фильтр по:

351–375 из 569 отзывов о курсе Fundamentals of Reinforcement Learning

автор: Mario A C S

16 окт. 2020 г.

Excellent course, great materials and explanations

автор: Mark P

19 мая 2020 г.

Excellent intro. Well paced, clear videos. Thanks!

автор: Arman K

31 дек. 2021 г.

T​his course was so helpful to me. Thank you all.

автор: Pratyush M

15 июня 2020 г.

some more practical implementation can be better.

автор: Maria D

23 мая 2020 г.

Challenging but helpful, awesome practical tasks!

автор: Deleted A

6 сент. 2019 г.

Builds a good foundation of basic concepts of RL.

автор: Marco G

7 янв. 2021 г.

clearly explained, nice textbook, good exercises

автор: Sriram R

24 авг. 2019 г.

Well organized course. Good pedagogy. Well done!

автор: Dongyu L

20 мая 2021 г.

Very good and clear introduction of the course.

автор: Shamuwel A A

24 нояб. 2020 г.

Fantastic beginning to a a very exciting topic.

автор: Tuyên Đ

24 авг. 2020 г.

perfect for who want to getting started with RL

автор: Debadri B

29 мая 2020 г.

Very good course for understanding basics of RL

автор: Xiyu Z

13 авг. 2021 г.

Great! I never learnt it so clearly in school.

автор: Charles X

19 июня 2021 г.

Very good one to get familiar with Q-learning.

автор: Eduardo F d S

26 июля 2020 г.

Good material and very well organized. Thanks!

автор: Sandro A

23 мар. 2020 г.

Great introduction to Reinforcement Learning!!

автор: Kyle W

16 февр. 2020 г.

I enjoy the programming assignments very much.

автор: Alejandro D

11 авг. 2019 г.

Excellent! Great content and delivery quality.

автор: Kyle A

15 авг. 2019 г.

great course!! thanks Adam, Martha and team!!

автор: Alexis O

24 апр. 2020 г.

Quality course to learn the fundamentals...!

автор: Raul D M

13 нояб. 2019 г.

One of the best courses I've had on Coursera

автор: Ram A

1 мая 2022 г.

Especially loved the hands on assignments!

автор: Carl

3 дек. 2020 г.

Solid course for laying foundations for RL

автор: asphinjohn

13 окт. 2020 г.

Had a clear idea of Reinforcement learning

автор: Holakou R

11 дек. 2019 г.

Fairly comprehensive. Easy/fast to follow.