Comentários e feedback de alunos de Prediction and Control with Function Approximation da instituição Universidade de AlbertaUniversidade de Alberta
Sobre o curso
Melhores avaliações
AC
1 de dez de 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.
SJ
24 de jun de 2020
Surely a level-up from the previous courses. This course adds to and extends what has been learned in courses 1 & 2 to a greater sphere of real-world problems. Great job Prof. Adam and Martha!
76 — 100 de 133 Avaliações para o Prediction and Control with Function Approximation
por Ola D
•15 de jun de 2022
Fantastic course with fantastic instructors
por İbrahim Y
•5 de out de 2020
the course is the intro for high level RL
por MJ A
•23 de jan de 2021
perfect and thank you for this course
por Teresa Y B
•11 de mai de 2020
Very Useful and Highly Recommend !!!
por Stewart A
•31 de out de 2019
Simply the best course on this topic.
por Farzad E b
•4 de ago de 2022
It was perfect, I really enjoyed it
por Junchao
•29 de mai de 2020
Very good and self-oriented course!
por Fernando A S G
•26 de mar de 2021
Excellent course! Thanks a lot!
por Wei J
•11 de out de 2020
It is a very perfect RL course.
por Antonis S
•30 de mai de 2020
Really a well-prepared course!
por Ignacio O
•29 de nov de 2019
Really good, I learned a lot.
por FREDERIC N
•2 de mai de 2020
Great speakers and content!
por Majd W
•1 de fev de 2020
Very practical course.
por 李谨杰
•17 de jun de 2020
Excellent class !!!
por Mohamed A
•11 de set de 2021
very good course
por Hugo T K
•18 de ago de 2020
Excellent course.
por Murtaza K B
•25 de abr de 2020
Excellent course
por Ivan M
•30 de ago de 2020
Just brilliant
por Juan “ L
•3 de ago de 2022
great course!
por Oriol A L
•19 de nov de 2020
Very good!
por Cheuk L Y
•8 de jul de 2020
Very good!
por Jialong F
•23 de fev de 2021
gooood!
por Justin O
•18 de mai de 2021
Great
por Artod
•27 de fev de 2021
Super
por Ananthapadmanaban, J
•19 de jul de 2020
I am disappointed with policy gradients being introduced on last week of the 3rd course. The instructors need to understand that 12 weeks is too much for introduction before starting a good project to implement the concepts with a hope to better understand them (course 4). Policy gradients should have been introduced in week 3/4 of course 2 itself. The content before that should be made more efficient (4 weeks to understand until q-learning/sarsa and 2 weeks to understand function approximation should be enough). I realized after course 2 that Andrew Ng has 3/4 videos on RL in the recently released ML class from Stanford. I am yet to go through them, but I feel they may explain these faster with same amount of rigour. However, the stanford class assignments are not public, which makes this course still useful because of the assignments. However, thanks to the instructors for this course.
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