Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.
The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.
교육 기관: Peter G•
The teachers are easy to like, but the course content is very lightweight and will mostly teach you terminology with no real understanding.
The worst part was the assignments, which could all be solved by a little copy/paste: I didn't learn anything useful by doing them. All the actual algorithms were supplied in a separate module. More than that, many of the suggested solutions were bad coding (like collapsing 50% of the data before training, or writing sixteen special cases rather than a general function) or pointless (like training a linear classifier on pixel data).
There are better courses out there.
교육 기관: Carlos K R•
Good course! The only major drawback is the requirement of Graphlab, which doesnt allow the student to fully understand the applications using real world software. Just recently, Dato (the company that owns graphlab) was purchased by Apple, and you can no longer buy a commercial licence to the software. Despite this, users cannot use Graphlab for commercial purposes, therefore rendering the software completely impractical for professionals. The specialization is designed to help you get a job (see capstone) yet the software currently in place is limiting.
교육 기관: Bruno C S d A•
I have no doubt teachers are excelent professionals in the area, as well as great machine learning enthusiasts. However, I did not like the fact that you get limited to learn how to use a paid and (very!) expensive platform, mostly because there are many other free packages available for machine learning. Ok, the platform offered makes things easier, but if you really want to learn machine learning, you can not be limited to a platform, acting as a robot just using pre-written functions in a black box.
교육 기관: Simiao L•
2 stars because the theoretical part is ok but programming assignments are waste of time. I'm not here (and paid) to be trained to use something the instructor is trying to SELL, nor will I ever recommend this product for commercial use. I will switch to other "not recommended" packages in the later parts of this specialization.
They should put the disclaimer for Graphlab Create in the specialization page so people can be aware of this.
Besides, the sound of that Giraffe toy is really, really annoying.
교육 기관: Ira T•
It really just touches a lot on different machine learning techniques and really just sets the stage for the higher courses. Unfortunately some of the chapters (especially deep learning) are so brief that it is really frustrating trying to complete the quiz and assignment. Also the course doesn't use open source tools but a trial version of a pretty expensive library.
교육 기관: Morten H•
Poorly executed. Constant differences in data. tiresome to watch two supposedly very intelligent instructors amuse themselves by saying Bro and Dude. The use og graphlab is unnecessary and adds a layer of complication which adds no future value to your toolkit. Probably a lot of better executed Machine Learning courses out there
교육 기관: Tom L•
I like the case-based approach--this course gives a nice albeit shallow overview. I don't like that one professor uses this course to push his startup by asking students to use graphlab. A more commonly used library would have been a much better choice. Parts of the course feel like a "Getting started with Graphlab" tutorial.
교육 기관: diego n•
Having done some other machine learning MOOCS , this course seemed rather basic to me and did not enjoy too much using non open-source software for the programming assignments. The material is nice, In this sense, I would have expected to 'default' to sci-kit learn and offer using graphlab create as optional.
교육 기관: Advait S•
While it was good for learning concepts I had real trouble with graphlab. Installation of graphlab never worked on my machine. I had to install VM just for being able to use graphlab. I really wish they had opted for more open source, free options or at least used ince such library along with graphlab.
교육 기관: Ziqian G•
There are big problems in this course, like the installation process should be given in a more specific and vivid way so that I would not have spent three days on it being a windows user...(update: still can't access jupyter notebook after trying installing ubuntu, vmware workstation, filezilla).
교육 기관: Sunaad R•
Too much dependency on Graphlab package is bad. If we are learning the concept, we should reduce the size of the sample data. We should be using generic open packages, so that our learning can be easily demonstrated anywhere (especially interviews), and not dependent on graphlab.
교육 기관: kunjan k•
The case study approach is a great idea.
But I wish the instructors were more candid about the tools that were in use. It seems dodgy that the instructor is a CEO of a commercial tool vendor and is "encouraging" students to use it.
The quizzes in the course were extremely shallow.
교육 기관: Raphael R•
The overall quality of the course is good, but in my opinion the level is quite low and there is less content then I expected. The assignments are more or less copy-paste or very repetitive. The 5-8 hour work per week are a joke, I never needed more than 2.5h per week.
교육 기관: Matthew F•
Focused too much on graphlab as opposed to the ML. If the course was titled ML with GraphLab I wouldn't mind (and wouldn't have signed up). The gaffs are kind of charming but really I would expect some of the videos to have had another take or two.
교육 기관: Joseph J F•
It is more a course in using the tools designed by the teachers than machine learning. It might do something for a less experienced user in programming, but I didn't find it much use. The overview of Machine Learning tasks isn't bad.
교육 기관: Andras H•
on one hand good... on other hand annoying ( mixing graphlab and turicreate... shitty wording of the assignment task, info added as side note which was vital for the assignments...etc.) The curse material would need a refresh.
교육 기관: Sunil T•
SFrame data do not support by an updated version of the Python, so student won't able to finish their assignments. So instructor need to update the materials and database which is supported by a new version of Python
교육 기관: Tudor S•
The Assignments and Quiz questions are hard to read and comprehend.
Although individually the course presentations are ok, overall this course isn't a very relevant or coherent introduction to Machine Learning.
교육 기관: Taylor I•
Feel like I have been duped in a way. No capstone project and you are pretty much forced to use Turi Create (proprietary/black-box version of pandas), which I found incredibly hard to install and use.
교육 기관: Ashley•
Content is outdated and should be revamp, the library use in this course is only for python 2.6 which is legacy and should be updated to latest python version using skicit learn instead of graphlab.
교육 기관: Arman A•
The course uses proprietary tools for machine learning and data manipulation, making it effectively useless! However, the material on describing the machine learning algorithms were excellent!
교육 기관: Annemarie S•
The instruction conceptually is fine, but I really disliked dealing with setting up Graph Lab Create and SFrames when we could have instead been using more commonly used open source software.
교육 기관: charan S•
If someone is looking for ML foundations and what is ML, they can choose this course. This is very basic course and i feel should be excluded from the ML specialization.
교육 기관: Eiaki M•
One would learn a thing or two, but the course is very sparse compared to other machine learning courses, and I didn't feel that it was worth the time and the cost.
교육 기관: Robert P M•
I do not like this course being tied to a commercial product. In my opinion it should be using an open source python library and not focusing on the Dato product.