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.
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.
par J N B P•
If you are familiar with the fundamental concepts of Clustering, unsupervised learning this course will help you move forward.
par Baubak G•
Need more details in the coarse. I think many of the topics need more working on, and are not sufficiently described.
par Valentina S•
Interesting content but explanations are less clear with respect to the other courses of the ML Specialization
par Michael L•
slightly repetitive of classification course with no real use-case value except lots of math..
par Rishabh s•
explained with pretty much good effort but can be improved if they focus on coding as well
par Volker H•
please rework in particular week 5, part 2
par Nicolas I•
A little too superficial and hand waving.
par Harsh A•
Too little "case-study" approach
par Stuart L•
the homework is getting easy
par Rohan G L•
I leave 2 stars as I learned a lot of new information and methods, and the theory and math behind them.
You will learn about Data Science and Machine Learning, but not much about Python.
The course is pretty much abandoned and outdated. Sframes and Turicreate packages (instructor's creations) are used instead of more universal packages. Installation in the beginning took some time and research. Many of the assignments have errors and bugs in the code that have not been updated. Forum assistance is abysmal for clarification or deeper questions. Many links are dead.
There are many times in the lectures where the instructors are writing several sentences in their handwriting on their notes instead of having the text ready to appear.
I would suggest using this course and series as a supplement to other information one as learned, not as an introduction for initial understanding. I found myself frustrated too many times.
par Ryan M•
While the topics covered in this course are arguably more complex than those in other courses in the Machine Learning specialization, I felt that the instructor did not do a good job covering the complicated material. There is a lot of statistics in this course, and the instructor seemed to assume that students would know many of the statistical terms and concepts without explaining them. I had to use a ton of outside resources to augment the videos presented as part of this course.
Furthermore, many of the assignments seemed to have errors in them. For the last programming assignment, there is no correct answer for at least one of the questions. Since there is no support from instructional staff or Coursera, this is a bit frustrating. Luckily you could pass the quiz without even answering that specific question.
par Pan W•
I give 5 star for the teacher, really approach having such a well-organized teaching material.
I also give -1 star for the homework assignment and its (almost) GraphLab only approach. Yes, it mentioned "alternative" approach (which is much more popular than GraphLab), but there are many bugs & trivial difficulties to get it through. With scikit-learn as a great open source package, the only reason (I suspect) to choose GraphLab is commercial purpose. For me, if the homework assignment is only instructed properly for loading data into Pandas, I can finish each programming assignment within 1 hour for sure using scikit learn; but now, it takes 30 minutes and I still cannot load the data correctly. I like to get a certificate, but it is not necessary and spending too much time is a waste on my time.
requires use of a programming library from a company that was sold and is unmaintained. Challenging to build the environment to run the homework code on my mac pro. An AMI is provided so you can try to do the assignments on a prebuilt machine. Anyway I've found the class quite a hassle.
par SHAHAPURKAR S M•
Course content is good but assignments are too lengthy and directions are not clear. Also, no support has been provided for non TuriCreate users. Students face a hard time in figuring out the Scikit-Learn implementations of the functions provided in the notebooks.
par Karl S•
For me, this course was disappointing. Here is why: First, the level, at which the course material is presented, is very low. It might be freshman level, but certainly not more. There are many buzzwords but no real explanations. The programming assignments are only doable because most of the work has been done by the people designing the assignments. There is very little left for the students. Furthermore, the procedures, that are already given, are not very well documented. Hence, a lot of guess work is required to figure out how things should work. Furthermore, little effort has been spent to structure the procedures that are already given. Altogether, this makes doing the programming assignments very unsatisfying.
Finally, the professor presenting the materials does not take part in the discussion forums. Contrary to other courses that I have attended at Coursera, this time the discussion forum was no help at all.
par Ricardo Y N•
some exercises only works if you have a Linux or MacOS, you could not resolve them if you have windows, the explanations are ok, I've never had an anwswer for my questions or issues on hte forum
par Kripakaran R•
I wish week4 and week5 were better. It felt so rushed, where most of the important things were covered.
This specialization is delayed for months now - very annoying! Don't give them money!
par Adrien L•
No good without the missing course and capstone projects