學生對 国立高等经济大学 提供的 Bayesian Methods for Machine Learning 的評價和反饋
課程概述
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JG
Nov 18, 2017
This course is little difficult. But I could find very helpful.\n\nAlso, I didn't find better course on Bayesian anywhere on the net. So I will recommend this if anyone wants to die into bayesian.
LB
Jun 07, 2019
Excellent course! The perfect balance of clear and relevant material and challenging but reasonable exercises. My only critique would be that one of the lecturers sounds very sleepy.
101 - Bayesian Methods for Machine Learning 的 125 個評論（共 157 個）
創建者 Chen Z
•Feb 11, 2020
Its a really good course, I learnt a lot
創建者 Савельев Н
•Dec 11, 2017
Best CS-related course on coursera yet
創建者 Arjun B
•Nov 25, 2017
Excellent content, quite challenging.
創建者 Truong D
•Sep 04, 2019
Easy way to approach the Probability
創建者 Oscar J P V
•Mar 05, 2020
Very complete course. Recommended!
創建者 François L
•Mar 07, 2019
Very tough but very interesting
創建者 Darwin D S P
•Aug 10, 2018
the jupyter file is outdated
創建者 Stephane H
•Nov 13, 2019
Great course, quite hard.
創建者 vania t
•May 21, 2020
excellent course!
創建者 M A B
•Jul 31, 2019
Amazing contents
創建者 Harshit S
•May 15, 2019
Awesome course !
創建者 Navruzbek
•Aug 17, 2018
Great course!!!!
創建者 Amulya R B
•Nov 05, 2017
Tough but a must
創建者 Xiaoying W
•May 07, 2020
Thanks a lot!
創建者 Jue W
•Apr 30, 2019
Very helpful!
創建者 RITICK G
•Dec 22, 2019
gfhgngfbfv
創建者 Goh
•Jul 04, 2019
Excellent!
創建者 Sankarshan M
•Jul 09, 2019
very good
創建者 Amrith S
•May 17, 2018
Succinct!
創建者 Kelvin L
•May 25, 2018
Cool!!
創建者 Hrushikesh L
•Jul 02, 2020
gOOD
創建者 Dipanjan D
•Jan 21, 2020
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創建者 Marcin L
•Nov 14, 2019
The course was great, I've learned a lot about Bayesian perspective on Machine Learning. The level was satisfying, tasks and quizzes were demanding. It has been very interesting material to learn about.
I would give 5 stars, but eventually gave 4 because it had two drawbacks. First is, assignments are written in tensorflow v1, and occasionally there were issues with compatibility in some libraries. I don't know when the codes were last time refreshed, but unfortunately open source technologies tend to become deprecated very quickly, and the time has already affected course materials. Secondly, some of the most important derivations were made on blackboard, and are not included in downloadable slides. I would really like to keep them in some files, but the're not available.
Apart from these minor drawbacks, it's still a great course and definitely worth learning from.
創建者 Erik B
•Jul 22, 2020
The material that was discussed was quite interesting. In particular, the variational inference, varfational auto encoders, and Gaussion process optimization.
I found the course material a bit lacking tough. There was one lecture where the main formulas for Guassian inference were derived that had a huge mistake in it. Also, sometimes, the assignments were totally unclear. The final project was a bit demotivating. Given the low quality of the pre-trained VAE, the results are not that good. If a pre-trained VAE was used, then why not simply use a bigger pre-trained VAE? Also, the final assignment was really easy and the whole peer review process felt a bit over the top. I must have spent more time in the forums getting my work reviewed than working on the final project.
創建者 Mehrdad S
•Sep 03, 2019
This is a great course for some of the advance topics in Baysian ML. The course starts off great and provides great explanation of the basic topics such as Conjugate, EM algorithm, etc. The related HW are also intelligently designed and fun to solve. But, as it reaches the weeks 5 and 6, things starts to fall apart and the materials are not presented and explained in the best possible way. I think the instructors try to teach many topics which requires a little bit of patience in a short amount of time. Overall, I believe its a course worthy of try, certainly provides great exposure to some of the advance topics but requires further follow ups and studies to completely digest all the materials.
