Aug 25, 2016
excellent material! It would be nice, however, to mention some reading material, books or articles, for those interested in the details and the theories behind the concepts presented in the course.
Jan 17, 2017
Excellent course, well thought out lectures and problem sets. The programming assignments offer an appropriate amount of guidance that allows the students to work through the material on their own.
von Marco A d S M•
Oct 20, 2017
As explicações poderiam ser um pouco mais detalhadas neste curto. Tive certa dificuldade em alguns conceitos apresentados, mais do que nos outros cursos.
von Michele P•
Sep 02, 2017
Advanced course. The material taught in this course is more advanced compared to Regression and Classification courses. You have to invest more time in respect to the previous courses. For some topics (LDA and hierarchical clustering) I had to look for other sources in order to understand the concepts properly. However, this course is a good introduction to clustering and retrieval.
von Martin B•
Apr 11, 2019
Greatly enjoyed it. As with the other courses in this specialization the discussion of the subjects is impeccable, especially if you've taken some preparatory mathematics courses. The reliance on Graphlab Create is a drag though.
von Christopher M•
Jul 01, 2019
Doesn't go quite as deep into the details as some of the other Machine Learning courses from the University of Washington do. Overall though, the course covers a LOT of ground. and provides exposure to many different topics.
I would have liked to have seen an Optional section on the derivation of some of the math that we were given functions for on the Expectation Maximization section. The models in the hierarchical clustering section take longer to fit than is necessary for a course like this (more than 40 times as long as the instructions say it should take), maybe a larger tolerance for convergence should be specified?
von Harsh A•
Jul 18, 2018
Too little "case-study" approach
von Ramesh S•
Aug 22, 2018
The clustering course covered a lot of topics, and it seemed a bit hurried too. I felt the quizzes could have been better worded to make it less confusing. LDA in particular deserved a better treatment - more could have been done I thought in terms of explaining the mathematics as well as the intuition (relative to MoG). Overall, it was a good course, but the best way to judge this would have been to ask a question like this - "what if people did clustering and retrieval even before they did other modules (regression and classification) - would the faculty have dealt the subject in the same way? ". My guess, is "unlikely" and that kinda explains what was missing !
von Baubak G•
Jul 11, 2018
Need more details in the coarse. I think many of the topics need more working on, and are not sufficiently described.
von Saeed S T•
Sep 08, 2016
Overall a good and useful course, however:
A) They could do a much better job regarding LDA, standard Gibbs sampling, and Bayesian model and inference. Many slides on these 3 topics only contained some text and the instructor tried to "verbally" visualize the related important concepts. Hence not a good use of a video session.
B) Week 1 and the 1st half of Week 6 were redundant.
C) It would be much better to have a 7-week course with more topics and may be with some optional videos on Bayesian model, HMM.
von Alexander S•
Aug 07, 2016
great course, but module 4 lacks a bit in structure. hard to follow. without the forum, it would not be possible to make it in time.
von Xiaosong L•
Aug 31, 2016
the homework is getting easy
von Michael L•
Mar 18, 2017
slightly repetitive of classification course with no real use-case value except lots of math..
von Diego T B•
Aug 28, 2016
The retrieval part of this course is great, it deserve five starts. The clustering part was going well until it reached LDA.
The LDA module is very poorly covered, and also very hard to understand. I had to watch the videos more than two times to try to figure out what was LDA, and a Quora article posted in the Forum could explain it much better.
Then we get to the Hierarchical Clustering module, which was the most poorly module in all this specialization. There is only one video talking about HMM models, and Markov Chains deserve at least one week to even get started with it. And to complete, there is just one Assignment with only 3 questions.
The specialization was going perfect until now. I am very disappointed with this course. I hope the last two courses are much better covered and not just ran over like this this one was.
von Volker H•
Jul 18, 2016
please rework in particular week 5, part 2
von Aayush G•
Nov 10, 2016
This specific course traded off depth and detail for breadth of topics. Too many ideas were quickly described and not really built up to my liking.
von Adrien S•
Oct 07, 2016
Feels like this course in the specialization was a bit rushed, compared to the first 3 courses. It had 2 modules (first & last) that were more like placeholders and the middle 4 modules went from concept to the maths behind the algorithm very quickly. It needs a bit of work on expanding the course and presenting a bit more slowly. Having said all that, the concepts and algorithms taught are very interesting and a good first step into the unsupervised learning section.
von Kayvan S•
Feb 15, 2018
Great course but I think the workload could be spread across the weeks more. Also, I had a lot of trouble with the sklearn toolkit (probably due to installation issues.).
von Piotr Ś•
Feb 15, 2017
Dependence on GraphLab technology is a big minus. The lectures are poorly balanced in terms of difficulty. Apart from that - interesting course, I'm glad I took it.
von Valentina S•
Aug 16, 2016
Interesting content but explanations are less clear with respect to the other courses of the ML Specialization
von Ahmed N•
Jul 18, 2017
The course focus on a great part of researches i have never read about them or had any idea about all of it. It doesn't focus on how we implement the core functions of machine learning but it was all of benefits and very very good to me i have learned a lot of things thank you all it's very tough and challenging course for me thank you all.
von Nicolas I•
Aug 31, 2016
A little too superficial and hand waving.
von Dmitri B•
Jun 21, 2017
Theory is cool but programming assignments requires proficient phyton knowledge. GraphLab helps but it wont be used in real life in our company :(
I found strange that often optional topics are major part of quiz, but anyway you should watch everything :)
von Oliverio J S J•
Jun 20, 2018
Some of the contents of this course are interesting, but it seems that this course has been very affected by the changes that forced the cancellation of the last two courses of the specialization. Apparently, they had to redo it and there are even two fake weeks (the first one and the last one). It is a pity that they did not want to spend more time to reorganize it.
von Dhanasekar S•
Dec 24, 2016
I have enrolled myself in the other Machine Learning courses offered by Uwash , but have to say this was not properly organized. I had got my certificates for the other courses easily , not because the contents was easy , but was easily understandable and well organized and there was a great sense of satisfaction after getting the certificate because of the knowledge gained.But unfortunately for this course , especially the week 4 and week 5 was lengthy and not up to the point and the quizzes were hence not seem to be related. So got my certificate after a bit of struggle.
I'm planning to see other online materials related to week 4 and week 5 , as couldn't completely understand from this one. If you can modify those two weeks, it would be great. I hope you continue the great work of illuminating millions of young people's interests through your great courses and organization. Thank you from the bottom of my heart.
von Dimitrios Z•
Jun 08, 2019
It has intresting theory but I believe the exercises need to be improvised. Maybe using Jupyter online and guiding the student to write code to solve the problems. In conclusion, I understood the basic theory but mostly that.
von Pavan B•
Jul 29, 2019
Few concepts were covered in hurry with lot of concepts described abruptly. It took a while for me to do research about those topics to catchup.