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A Complete Reinforcement Learning System (Capstone)(으)로 돌아가기

앨버타 대학교의 A Complete Reinforcement Learning System (Capstone) 학습자 리뷰 및 피드백

561개의 평가
118개의 리뷰

강좌 소개

In this final course, you will put together your knowledge from Courses 1, 2 and 3 to implement a complete RL solution to a problem. This capstone will let you see how each component---problem formulation, algorithm selection, parameter selection and representation design---fits together into a complete solution, and how to make appropriate choices when deploying RL in the real world. This project will require you to implement both the environment to stimulate your problem, and a control agent with Neural Network function approximation. In addition, you will conduct a scientific study of your learning system to develop your ability to assess the robustness of RL agents. To use RL in the real world, it is critical to (a) appropriately formalize the problem as an MDP, (b) select appropriate algorithms, (c ) identify what choices in your implementation will have large impacts on performance and (d) validate the expected behaviour of your algorithms. This capstone is valuable for anyone who is planning on using RL to solve real problems. To be successful in this course, you will need to have completed Courses 1, 2, and 3 of this Specialization or the equivalent. By the end of this course, you will be able to: Complete an RL solution to a problem, starting from problem formulation, appropriate algorithm selection and implementation and empirical study into the effectiveness of the solution....

최상위 리뷰


2020년 4월 27일

This is the final chapter. It is one of the easiest and it was fun doing that lunar landing project. This specialisation is the best for a person taking baby steps in the reinforcement learning.


2020년 2월 26일

Great course for learning the fundamentals. I liked that it tied into function approximation for deep reinforcement learning. The text book made the fundamental concepts more clear.

필터링 기준:

A Complete Reinforcement Learning System (Capstone)의 120개 리뷰 중 76~100

교육 기관: Fintan K

2020년 11월 24일

Brilliant Course All Round!

교육 기관: RICARDO A F S

2020년 11월 22일

Let's go to the moon!

교육 기관: Ryan Y

2021년 3월 4일

Thank you very much!

교육 기관: dariojavo

2020년 10월 18일

Excellent material!

교육 기관: Jose

2020년 6월 29일

excellent course

교육 기관: BC

2020년 5월 6일

Excellent course

교육 기관: RUI D

2021년 8월 2일

Nice Course!

교육 기관: Yanlin L

2020년 4월 19일


교육 기관: Chang, W C

2019년 11월 8일


교육 기관: 남상혁

2021년 1월 18일

Very good

교육 기관: Tran M D

2020년 5월 22일


교육 기관: A4

2020년 1월 1일


교육 기관: ARTEM B

2021년 3월 1일


교육 기관: Justin O

2021년 5월 22일


교육 기관: Adrian Y X

2020년 4월 4일

I will write a longer review for the entire Specialization later, but this course does well to sum up all of the other progress you've had made thus far on the Specialization. However, you'll find that from Course 2 onwards (and this one especially), very little hand holding is given for the programming assignments. Command of numpy and python at good level are expected. Personally, having worked with OpenAI gyms before starting this specialization helped me immensely. As the instructors state, this course lays the foundation for future studies. The field of RL is simply so complex that even foundational work is challenging. Overall, a great course.

교육 기관: Steven W

2021년 5월 11일

They mostly discuss the importance of real world experience and hyperparameter tuning in this class. The content it did have was solid and the instructors were great. The "capstone" was creating an agent to solve the Moon Lander problem, and much of the code was already written.

I would have really preferred getting experience with a real RL framework like RLLib or acme, rather than the toy libraries used by the book. It would have also been really nice to have a little more freedom and challenge, such as making us actually create an agent to solve an MDP of our own choosing and definition.

교육 기관: Henry C

2021년 10월 16일

A decent course to wrap up the RL specialization, with a "project" that demonstrates a "real-world" application of RL.

The word "project" is in quotes because it is structured as a (short) series of fairly short assignments with very heavy hand-holding, so very similar to previous courses.

My only complaints with this course are that the project is a bit too hand-holdy and that the course overall is quite short and thin in content. I would estimate that this course is around 1/3 the length of the previous courses in this series.

교육 기관: Jing Z

2020년 6월 2일

The project is a decent example to go through in order to review what we learned from previous courses. However there are few key things supposed to be addressed as well: 1) What exactly the reward function is in the final project (C4M1 practice is badly designed); 2) How can we build an environment on our own; 3) Apart from Mean Squared Value Error to be minimized, what are other loss functions to choose from and what's the consideration behind.

교육 기관: Francisco M

2022년 7월 12일

I am a recently junior researcher in the Optimization field, approaching predictive and prescriptive online retail problems. Therefore, I truly believe this complete reinforcement learning specialization gave me the foundations to evolve my research in this domain. About the structure and contents of the specialization, I think it is very well organized in the 4 main courses. Thanks to the team.

교육 기관: Dmitry S

2020년 1월 10일

Good course. Summarises and puts everything in context. But would benefit from having larger programming assignments (which would make it more challenging as well) when less things are provided out of the box, and from a bit more extended and systematic overview and walk-through of the material.

교육 기관: Ahmed S S A

2020년 3월 5일

Great course, thanks a lot really. But I do hope if we did visualize the environment to see how my agent behaves and then saves the RL agent to use it offline after being trained. Really thank you so much for making RL clear to me and interesting too :) <3

교육 기관: Alaaeldin Z

2021년 5월 24일

I liked the project. I hoped it would be harder and enable the students to design the whole agent and environment code and be evaluated with a human grader. But overall, I was able to practice the concepts I have learnt throughout the specialization.

교육 기관: Surya K

2020년 5월 3일

A cherry on top of the cake. This course helped me understand how to think about a novel problem and formulate and build an RL system from scratch. I thank Course Instructors, University of Alberta, and Coursera for this beautiful specialization.

교육 기관: Lik M C

2020년 1월 23일

The project is interesting. But the implementation left as assignments is too simple. There are too many guidance running in assignments. If more flexibility is allowed in implementing the project, it should be even more interesting.

교육 기관: Mateusz K

2019년 11월 16일

In my opinion, the capstone should've included more development and or programming. I liked having to develop NN action-value function approximator, but the parameter study was a bit too simple (should've had more code content).