Oct 17, 2016
Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much
Dec 20, 2016
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.
교육 기관: Toma K•
Jun 11, 2019
Warning! I paid for the specialization and now it tells me that the course ended 2 months ago!! i can't complete quizes which is why i paid!!! no options available to contact support.... no refund available....
교육 기관: Pablo S•
Jul 22, 2019
I should have read the negative reviews before wasting two full days trying, and failing, to install the required software. I urge anyone reading this to avoid this course and look for alternatives.
교육 기관: Xing W•
Jul 03, 2016
I was expecting to solve problems using more open-sourced package. Unfortunately, I feel this series of courses are more of an advertisement for the instructor's software company.
교육 기관: Eduardo R R•
Sep 23, 2015
This course rely on commercial library. I am sorry, I don't believe the convenience of a commercial library is good for your learning. You may end up locked in.
교육 기관: Dmitri K•
May 27, 2016
The whole course based on some proprietary software. In general, it seems that the main goal of the course is promote that software.
교육 기관: sravan•
Oct 13, 2016
there is no proper documentation.
at least there should be some clear instructions for first program
교육 기관: Mario L•
Nov 24, 2015
I dont like the tools they used, it seems like a promotion for their company.
교육 기관: Lester L•
Mar 21, 2020
Not made for Windows, you need a linux or mac VM to apply this course.
교육 기관: Tim B•
Jun 04, 2019
Complete waste of time until it is written using open-source packages.
교육 기관: Phillip B•
Sep 25, 2015
Would have greatly preferred if open source tools were used.
교육 기관: Chandrakant M•
Sep 06, 2016
I felt that I paid for demo of the Dato/Turi.
교육 기관: Nitin K•
Sep 12, 2019
Not good support to learning process.
교육 기관: Rohit•
Apr 19, 2020
This course is pretty good for beginners. All domains are explained briefly as an introduction. The best part about this course is very good hands-on sessions which are really helpful to understand concepts. The course is not very detailed but it's very good to start with. Looking forward to quality courses ahead in this specialization.
교육 기관: Shibhikkiran D•
Apr 13, 2019
This is course is very informative for a beginner. It helps you to get up and running quick provided you have little basics on Python. You should( sideline on your own interest) also pickup Statistics/Math concepts along each module to make a rewarding experience as you progress through this course.
교육 기관: Diogo J A P•
Feb 15, 2016
With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!
교육 기관: Karthik M•
Dec 27, 2018
A good course to understand the basics of Machine Learning. The only issue is the use of Graphlab library. Since it only works on Python 2.7, it is not convenient for people who prefer Python 3
교육 기관: Alexandru B•
Jan 21, 2016
Great course. Very informative and inspirational. I got tons of ideas from it! Thank you
교육 기관: Mallikarjuna R V•
Jan 17, 2019
Wonderful opportunity to learn and execute hands on coding of Machine Learning. The amazing task that Machine Learning methods and algorithms does behind scene is understood for the following cases / intelligent applications:
1. Regression (e.g. Predicting House Price etc.)
2. Classification (e.g. Product review sentiment, Spam detection, Medical diagnosis etc.)
3. Clustering and Similarity (e.g. Grouping news articles)
4. Recommender (e.g. Amazon personalized product recommendations, Netflix personalized Movie recommendations etc.)
5. Deep Learning and Deep Features (e.g. Google image search, Image-based filtering etc.)
The main challenge for me was to code using “Python3, Pandas and SciKit-Learn” instead of “Python2, GraphLab Create and SFrame”. I am now confident to develop intelligent applications based on Machine Learning. Thanks to Professors (Emily and Carlos) and to Ashok Leyland-HR for giving me this opportunity.
교육 기관: akashkr1498•
Jan 18, 2019
lacture was good but one point i want to share to you don't use rare tools for assignment personally i faced lots of problem while installing graphlab better to switch to some common tools like sklearn python platform .
교육 기관: Yuvraj S•
Feb 01, 2019
It is a good course if we take into account the foundational part. But since only one library has been used to solve the issues, one does not explore and write their own functions.
교육 기관: Nik M N N G•
Feb 11, 2020
The material in this course severely needs an update. Some of the code examples (not from the video, because the video is obviously from old materials) are problematic. It's an interesting experience to learn a new library but I wish the experience is different. The quiz should be tougher in my honest opinion.
교육 기관: Jaime R•
Dec 17, 2018
Great introduction course. However, getting the notebooks to work with Graphlab is a real pain. The notebook exercises are also mostly make-work rather than real explorations. The explanations and the notebooks themselves are pretty good though
교육 기관: Jefferson N•
Feb 13, 2019
A good course, but the tools are a bit dated and it's showing its age.
교육 기관: Malik M W•
Mar 31, 2020
I think this course is outdated as they are using python 2 also the platform they use for machine learning only supported by python 2. Due to these limitations, I too was unable to continue this course. Because every time you have to work with new libraries you have to uninstall python 2 and reinstall python 3.
교육 기관: Vakkalagadda A r•
Dec 28, 2015
Instructors or TAs are not available in discussion forums. and the course is focussed on promoting "graph lab" proprietary package of the course sponsor. Maybe you can have a look, not beneficial if you are serious about learning ML.