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Opiniones y comentarios de aprendices correspondientes a Fundamentals of Reinforcement Learning por parte de Universidad de Alberta

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513 reseña

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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....

Principales reseñas

6 de jul. de 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 de abr. de 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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301 - 325 de 512 revisiones para Fundamentals of Reinforcement Learning

por Jicheng F

11 de jul. de 2020

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

por Chanon K

28 de jun. de 2020

A great course that really focusing on fundamentals of RL

por Adarsh

16 de may. de 2020

very good course .

very well explained by Adam and Martha

por Pradyumna M

3 de abr. de 2020

Amazing course with optimum blend of theory and practice.

por Oleksandr M

6 de oct. de 2019

Great course! Good explanations, interesting assignments.

por Garrett S

10 de ago. de 2019

Explained in a very simple way, with helpful assignments.

por Sergio B

22 de may. de 2020

Outstanding explanations and assignments. Very hands-on.

por Da

30 de oct. de 2019

Really interesting course based on Sutton and Burto book

por Chang, W C

24 de oct. de 2019

I like the concept are represented in visualization way.

por Marcelo G P d L

25 de jun. de 2021

This is a great introduction to Reinforcement Learning!

por Ignacio O

22 de ago. de 2019

Excellent beginners course of a very interesting topic!

por Trevor M

28 de ago. de 2019

Excellent material paired with excellent instruction.

por Salomon T

12 de jul. de 2020

Great course, that gives a thorough foundation on RL!

por Antonio P

11 de nov. de 2019

Great introductional course on Reinforcement Learning

por Gyanendra D D

11 de dic. de 2020

Very good course if you follow along with the book.

por Chirag M

5 de nov. de 2020

Great course! A lot of good material and insights!

por Jingxin X

17 de may. de 2020

Very helpful hands-on experience with the notebooks

por Yue Z

9 de feb. de 2020

Everything is good except the peer review question.

por Jaime C

27 de mar. de 2021

Excellent, good combination of theory and practice

por Mario A C S

16 de oct. de 2020

Excellent course, great materials and explanations

por Mark P

19 de may. de 2020

Excellent intro. Well paced, clear videos. Thanks!

por Pratyush M

15 de jun. de 2020

some more practical implementation can be better.

por Maria D

23 de may. de 2020

Challenging but helpful, awesome practical tasks!

por Deleted A

6 de sep. de 2019

Builds a good foundation of basic concepts of RL.

por Marco G

7 de ene. de 2021

clearly explained, nice textbook, good exercises