Opiniones y comentarios de aprendices correspondientes a Sample-based Learning Methods por parte de Universidad de Alberta
Acerca del Curso
Principales reseñas
Great course, giving it 5 stars though it deserves both because the assignments have some serious issues that shouldn't actually be a matter. All the other parts are amazing though. Good job
Really great resource to follow along the RL Book. IMP Suggestion: Do not skip the reading assignments, they are really helpful and following the videos and assignments becomes easy.
126 - 150 de 203 revisiones para Sample-based Learning Methods
por Eleni F
•i really enjoy it!
por Mohamed A
•very good course
por Guoxiang Z
•Very nice course!
por ABHILASH N
•Brilliant Course!
por Antoni S D S
•Curso muito bom!
por Julio E F
•Amazing course!
por Santiago M C
•excelent course
por Trần Q M
•wondrous course
por Max L
•great lecture
por RICARDO A F S
•Great course
por Antonio P
•Great Course
por John H
•It was good.
por Charles X
•Good course
por Oren
•Fun course!
por Jialong F
•learn much
por Sohail R
•Fantastic!
por LuSheng Y
•Very good.
por Oriol A L
•Very good
por Pouya E
•Amazing!
por ARTEM B
•Perfect
por Justin O
•Great
por chao p
•Great
por Alejandro S H
•The course material are great. You will learn a lot from the assignments and from the book. The videos are a good refresher of what you'll read in the book, sometimes with improved animated visuals. However, I've a few nitpicks that prevent me from giving it 5 stars. (1) The instructors do not interact much with the students in the forum (if at all). (2) There's an inaccuracy in one of the videos that (as of the instant I'm doing this review) hasn't been fixed yet. (3) The quizzes sometime ask for questions that are NOT in the assigned homework materials (I'm thinking now about a question about prioritized sweeping in the planning section, but there are others). This is not a big deal, the questions will ring a bell immediately and you will find the section of the book where the answer lies (or you will answer out of common sense). (4) There's a video about applying RL in continuous tasks in robotics (purely motivational, not part of the syllabus) that is missing the second part. I'm guessing it's in the next course?
por Oscar R R M
•I have to admit that the practical programming tasks are excellent. The discussions sections are well maintained by professors. The recommended readings are good. The exams are fine but some questions can be a bit confusing or not clear enough.
I consider the lectures to be the weakest part of this course. In lectures, they only provide a short summary of what is already written in the book, which may be useful for some people, but I prefer the old way of long lectures in a blackboard full of mathematical proofs and historical notes providing true understanding of the topic. The invited lecturers are pretty good, since they show some historical notes or cutting edge projects.
So far this is the best course I have found on this topic.
por Neil S
•This is THE course to go with Sutton & Barto's Reinforcement Learning: An Introduction.
It's great to be able to repeat the examples from the book and end up writing code that outputs the same diagrams for e.g. Dyna-Q comparisons for planning. The notebooks strike a good balance between hand-holding for new topics and letting you make your own msitakes and learn from them.
I would rate five stars, but decided to drop one for now as there are still some glitches in the coding of Notebook assignments, requiring work-arounds communicated in the course forums. I hope these will be worked on and the course materials polished to perfection in future.
Coursera Footer
