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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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308 revisiones

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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 revisiones

NH

Apr 08, 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!

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

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176 - 200 de 308 revisiones para Fundamentals of Reinforcement Learning

por Joost G

Mar 26, 2020

Interesting lectures and good quizzes+programming exercises.

por Marius L

Sep 05, 2019

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

por Mr. D S J D P

Jun 05, 2020

I struggled in programming part , but a very efficient tool

por Ruosen L

Apr 03, 2020

Spent tooooooo much time on reading materials than imagine.

por alex x

May 21, 2020

Very good course, hope there will be more course like this

por Chanon K

Jun 28, 2020

A great course that really focusing on fundamentals of RL

por Adarsh

May 16, 2020

very good course .

very well explained by Adam and Martha

por Pradyumna M

Apr 03, 2020

Amazing course with optimum blend of theory and practice.

por Oleksandr M

Oct 06, 2019

Great course! Good explanations, interesting assignments.

por Garrett S

Aug 10, 2019

Explained in a very simple way, with helpful assignments.

por Sergio E B

May 22, 2020

Outstanding explanations and assignments. Very hands-on.

por David P

Oct 30, 2019

Really interesting course based on Sutton and Burto book

por Chang, W C

Oct 24, 2019

I like the concept are represented in visualization way.

por Ignacio O

Aug 23, 2019

Excellent beginners course of a very interesting topic!

por Trevor M

Aug 28, 2019

Excellent material paired with excellent instruction.

por Antonio P

Nov 11, 2019

Great introductional course on Reinforcement Learning

por Jingxin X

May 17, 2020

Very helpful hands-on experience with the notebooks

por Yue Z

Feb 09, 2020

Everything is good except the peer review question.

por Daniel D V

Aug 24, 2019

Very well explained, with amazing examples. Thanks!

por Mark P

May 19, 2020

Excellent intro. Well paced, clear videos. Thanks!

por Pratyush M

Jun 15, 2020

some more practical implementation can be better.

por Maria D

May 23, 2020

Challenging but helpful, awesome practical tasks!

por Ankith M

Sep 07, 2019

Builds a good foundation of basic concepts of RL.

por Sriram R

Aug 24, 2019

Well organized course. Good pedagogy. Well done!

por Debadri B

May 29, 2020

Very good course for understanding basics of RL