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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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315 revisiones

Acerca del Curso

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

AT

Jul 07, 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.

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!

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51 - 75 de 315 revisiones para Fundamentals of Reinforcement Learning

por Zhuang J

Mar 24, 2020

You really need to understand fundamentals before kick start for any real world reinforcement learning problem. That's why this course is very essential. Plus it also provides programming tasks and multi-choice question sheet to deepen your understanding about theories. Great! Looking forward to move on for next series!

por Shashank S

Apr 13, 2020

This course was a great first introduction to reinforcement learning! The course instructors make the material very accessible and the course follows the textbook very closely. I'd definitely recommend it to anyone trying to understand reinforcement learning and I personally plan to complete the entire specialization.

por Stelios S

May 11, 2020

This is the BEST course I've taken from Coursera, period. The level of explanation, the usage of mathematically precise terminology, the walking through of the algorithms, the summaries were all top-notch. This course will be my reference when I forget something in the future. I can't thank the creators enough.

por Ali N

Apr 01, 2020

It was a very good course, I had read Sutton's book first. But I must say that after completing this course, I learned the concepts of the book well. Although the exercises were a bit tough, they covered the topics well and increased learning at a faster rate.

For anyone interested, I recommend this course.

por Иванов К С

Aug 29, 2019

It's difficult to estimate this course because it's based on the book. I mean, 90% of materials i've seen on videos were on the book. That's very unusual, but effective. However, i've learned necessary information and python tasks were useful and interesting. I'll take the next course and will see.

por Nicolas T

Apr 26, 2020

Great course! The idea of suggesting reading before the videos gives a huge boost to the depth of the class. This, with the "not-too-straightforward-quizzes", and the assignments, makes it a real deep class, from which I'll probably learn and retain more than most online courses. Good job!

por Anton P

Dec 15, 2019

It is a very well laid out and taught course. The instructors make the material accessible with a bit of a mathematics background, or a willingness to learn. I will be taking every machine learning course I can from AMII and the UofA if the rest of the courses are of the same quality.

por Sandesh J

Jun 01, 2020

One of the best available courses on Reinforcement Learning. The instructors have explained all the underlying topics elegantly. Good blend of theory and numerical in assignments and programming problems. Moreover, the assignments have covered different perspectives on these topics.

por Giulio C

Jun 25, 2020

Amazing course!

The book, on which this course is based, is a bible for reinforcement learning. Anyway, it could be hard to understand. The lectures of the course eliminate all doubts and consolidate all the concepts, ensuring a complete comprehension on the subject.

Thank you!

por Bae,Bongsung

Apr 20, 2020

Great starting point for learning Reinforcement Learning. Anyone who is interested in the state-of-the-art RL techniques should take this course first, or they will have hard time getting through the more applied and sophisticated concepts found in the tech blogs or papers.

por Majd W

Oct 24, 2019

The thing that makes this course outstand among other Coursera courses is that it is based on a book. That gives you more information if you need it.

One problem that I guess will be solved in the future is that there is a bug in the Programming Assignment submission code.

por Juan C E

Feb 09, 2020

Excellent course. Excellent teachers. I love the introduction sections, in which you're presented what you'll learn in each video, and the summary section. The animated slides are also very professional. Very thorough coverage of the RL book. Congratulations!!!

por Yover M C C

Mar 02, 2020

Excelente curso, aprendí los conceptos de aprendizaje por refuerzo con gran base teórica, el material del curso es muy bueno y la calidad de las lecturas es de excelente nivel. Muy recomendado, ahora a aprender más y a desarrollar sistemas inteligentes :).

por Evgeny S

Apr 18, 2020

I enjoyed the course. I would have preferred a bit more in-depth look at the algorithms and technical details, but, on the other hand, it was also interesting to go and figure out these contraction mapping arguments on your own. Overall, very good.

por Leelamohan

Feb 16, 2020

I had learned a clear understanding of terminology and the formulas of value function, action-value function, optimal value function, Bellman's equation, policy evaluation and iteration. It's a must go through course for Reinforcement Learning

por Damian K

Sep 01, 2019

Slow means smooth. Smooth means fast. This course introduces you efficiently into the world of RL. And this is what you want. Everything is perfectly to the point. All exercise are here to boost your understanding. Highly recommended.

por Min-Chun W

May 31, 2020

Course contents are good and easy to understand. Textbook is really a good supplement to lecture videos. Assignment difficulties are between being easy and moderate. It's really fun and encouraging when completing the assignments.

por Naveen M N S

Sep 09, 2019

The pattern of this course is amazing. Each video is short and has a specific objective that's clearly stated. This approach to teaching made tough topics look easy. Assignments and quizzes were doable. Amazing experience overall!

por Surya K S

Apr 05, 2020

Course was beautifully made. I tried to learn RL from multiple different courses but I couldn't understand them. This course was different however, the assignments were made in a way that helped me understand concepts concretely.

por Guto L S

May 27, 2020

Very good course! It introduces basic concepts necessary to understand the basic reinforcement learning algorithms. The course is well structured, and the practical activities help a lot to fix the studied content.

por VBz

Oct 22, 2019

Short videos, with list of objectives at the beginning and recap and the end, and clear explanations in between. In my opinion, all teachers should watch these videos to get an example on how good courses are done.

por Nhu N A

May 30, 2020

The reading is a little bit challenging, but everything was explained very clearly with helpful examples in lecture videos. Absolutely recommend for someone who want to explore the field of Reinforcement Learning.

por Shahriyar R

Sep 22, 2019

Extremely useful course. Especially the format is very effective. First read the book, then listen the extra explanations and write Python code. Concepts are really clear for me now. Thanks for such amazing work.

por Tristan S

Apr 07, 2020

Great course for learning fundamentals. My only complaint is that I don't quite feel comfortable implementing what I have learned with coding yet. Maybe as I progress in the specialization this will get better.

por Nick S

Mar 11, 2020

Excellent course, with an excellent explaination of Markov Decision Process and Dynamic Programming by the 2 teachers. The quizzes and the final exercice are challenging and make you search in the text book.