创建者 Evaristo C•
Sep 17, 2017
This is THE BEST course in Recommendation Systems. Probably getting a bit outdated as the field is moving rapidly into deep learning and other techniques, but the problems faced by any recommendation system developer would be the same - ratings measurement, sparse matrices, ranking metrics... And THAT is probably the best contribution of the whole training: not only talking about the methods but pin-pointing the main REAL problems to solve.
创建者 Ankur S•
Jan 26, 2019
Great course to understand the fundamentals of recommender systems, as well the diversity & challenges of different recommender systems. The interviews with people from relevant academic fields & industry were particularly useful
I really wish that the programming exercises would be in Python. And that more details on how to implement them (the actual modeling of the algorithms etc) was delved into greater detail.
创建者 Su L•
Sep 12, 2019
It will be great, if we can do honor's track with Python or R
创建者 Daniel P•
Jan 07, 2018
Very interesting topic which I was really stoked to learn but unfortunately this course is missing the deep insight into the algorithms, it explains just one algorithm and its variations. The content is overall to little for 6 weeks course and the honor's assignment has very bad task description with errors and lack of validating possibilities.
创建者 Nicolás A•
Jul 24, 2018
-some videos need better editing
-should go into more mathematical detail for the matrix factorization techniques
创建者 Amine D•
Dec 27, 2017
the way of explaining every concept is very boring
创建者 Keshaw S•
Mar 07, 2018
Based on my experience with the previous courses in this specialization, I was very positively surprised by the amount and depth of material provided in this course. It covers almost everything that is there to be known. The comprehensive interviews are a big plus point. Also, this course provides guidelines as to how to develop, employ and evaluate a recommender system in real life. I would definitely recommend anyone interested in the field to take this course.
创建者 Blake C•
Jan 13, 2018
Great course. Professors do an excellent job of breaking down this stuff into digestible bits without losing much substance. Highly recommend. You'll need to do some outside exploration and learning though.
Jul 19, 2017
great courses! They invite a lot of interviews to let me understand the sea of recommend system!
创建者 Joeri K•
Mar 28, 2019
Great to have people from industry to talk about recommenders as well. Thanks a lot!
创建者 Sanjay K•
Dec 05, 2017
Awesome course especially for those doing Ph.D in recommender systems
创建者 Ziling C•
Mar 29, 2020
so very helpful!
创建者 Rahul G•
Feb 19, 2018
The Hybrid recommenders i.e. Week 4 needs more explanation especially what is Tensor factorization etc, Week 4 was difficult to grasp. Week 5 and Week 6 was informative especially the LinkedIn video and Learning to Rank: Interview with Xavier Amatriain in which a problem was discussed of having that popularity vs Ranking issue.
Thanks it was quite a lot new things to learn ! My Rating 4.5
创建者 Nora P H L•
Apr 24, 2020
The content is really good, but overall the interviews with experts in the field are the best of this course.
创建者 Alberto G•
Jun 10, 2018
Programming Assignments are not clear enough and the quiz for the last one seems to be a bit off.
Aug 14, 2017
Interview with Francesco Ricci
is very knowledgeable about context aware Recommender System.
创建者 LU W•
Aug 25, 2018
It would be better if explaining how to build latent features
创建者 Siwei Y•
Jun 29, 2017
内容还是蛮有意思的。 就是 Interview 太多, 而且interview 的人的 上课水平参差不齐， 所以干货 不多。 另外 希望honor assignment 的 参考结果 应该比较 reproducible， 否则很难知道自己的 code 错在哪里。
Content is really interesting, But there are too much interviews, to give students more systematical impression. Besides that , I hope that the example output of honor assigment should be more reproducible , otherwise it is hardly to know if our code is corrrect.
Jun 16, 2017
The topics that were covered were done well, but I was expecting (and hoping for) way more on probabilistic matrix factorization (I still struggle to understand how it differs from regular MF) and Boltzmann machines. Also, only one assignment in the standard track? And you couldn't auto-grade standard track assignments and quizzes without charging a fee? Weak
创建者 Kemal C K•
Dec 28, 2017
Few quizes. Easy tests. We need more information on the core techniques.
创建者 Moustafa M•
Apr 18, 2020
The HWs for the Honor track had mistakes
创建者 Daniel M•
Aug 31, 2019
Content okay, if a little basic. Second honor's track assignment is a complete mess; can't even build properly. Complaints on discussion board have gone unanswered for months.
创建者 PRATIK K C•
Jun 09, 2020
Could have been better