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Learner Reviews & Feedback for Prediction and Control with Function Approximation by University of Alberta

4.8
stars
826 ratings

About the Course

In this course, you will learn how to solve problems with large, high-dimensional, and potentially infinite state spaces. You will see that
estimating value functions can be cast as a supervised learning problem---function approximation---allowing you to build agents that carefully
balance generalization and discrimination in order to maximize reward. We will begin this journey by investigating how our policy evaluation or
prediction methods like Monte Carlo and TD can be extended to the function approximation setting. You will learn about feature construction
techniques for RL, and representation learning via neural networks and backprop. We conclude this course with a deep-dive i...
...

Top reviews

AC

Dec 1, 2019

Well peaced and thoughtfully explained course. Highly recommended for anyone willing to set solid grounding in Reinforcement Learning. Thank you Coursera and Univ. of Alberta for the masterclass.

WP

Apr 11, 2020

Difficult but excellent and impressing. Human being is incredible creating such ideas. This course shows a way to the state when all such ingenious ideas will be created by self learning algorithms.

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126 - 146 of 146 Reviews for Prediction and Control with Function Approximation

By Bhavesh A

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Dec 17, 2024

Everything is great about this course except the policy gradient part, the need of policy gradients and why we should use policy gradients while we can use function approximation and (to compute policy gradients, we anyways have to compute function approximation).

By Amit J

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Mar 17, 2021

Lecture quality could have been better. They look like practiced monologues rather than a class where a teacher is trying (hard) to explain a concept. If one has to wait for assignment to get the full grasp, it doesn't reflect too well on the instructors.

By Lik M C

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Jan 18, 2020

The course is still good. But the assignment is not as good as course 1 and 2. In fact, the contents of the course are getting complicated and interesting as well. But the assignments are relatively simple.

By Mark P

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Aug 17, 2020

Solid intro course. Wish we covered more using neural nets. The neural net equations used very non-standard notation. Wish the assignments were a little more creative. Too much grid world.

By Anton P

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Apr 12, 2020

There is a lot of material covered in the course. Be aware the pace picks up considerably from the first two courses. This said, it is a worthwhile course to take.

By Vladyslav Y

•

Sep 8, 2020

I wish agents that are based on visual information (with the usage of CNN) would be included in the course. But overall that was really great!

By Sharang P

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Feb 27, 2020

more detailed explanation of some of the assignments and how state values are got with tile coding but overall a great experience!

By Jerome b

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Apr 9, 2020

Great course, based on the reference book about reinforcement learning. A must for anyone interested in machine learning.

By Rajesh M

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Apr 17, 2020

I loved the course videos and programming assignments. The only suggestion would be to go a little deeper in the videos.

By SCOTT A

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Aug 5, 2020

This was a good course but I really struggled to understand how each of the value functions translated into code.

By Muhammed A Ç

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Sep 4, 2021

Programming exercises are not self explaining. But instructors are explaining concept in a perfect way

By Pouya E

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Dec 2, 2020

Great overall. The content on policy gradient could be expanded, some details were delivered hastily.

By Rish K

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May 19, 2020

The average reward and differential return needs to be explained more thoroughly

By Ramaz J

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Oct 17, 2019

Course is great! Maybe some slides would be helpful not to forget.

By Charles X

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Jun 21, 2021

Gets hard to understand.

By Quarup B

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Jul 25, 2021

Content is great, but the text is super dense -- slow read for me. The lectures are much clearer, although also a bit dense / quick paced to retain the information long term (especially if one wishes to skip the reading).

By Prashant M

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Jun 7, 2020

great course material but you need read the RL book through out the course. Also assignments are bit difficult, oops concept is mandatory.

By Joe M

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May 16, 2024

The content is good. The lectures are poor with the instructors doing little explanation other than reading equations off slides.

By Justin N

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Mar 31, 2020

Lectures are pretty good, but the programming exercises are extremely easy. All of the problems are rather contrived as well.

By Yassine B

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May 4, 2020

I think It must be more deep neural networks dedicated course and not focus on coarse and tile coding!!!

By Bernard C

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May 24, 2020

Course was good, but assignments were not well constructed. Problems with the unit tests were frequent.