No Open Source Libraries, this course is not educational; it is a sales pitch to use their expensive software. Good luck having an employer pay this amount of money for software when they can hire employees that can use free open source libraries.

The fact that the class uses GraphLab instead of pandas/numpy/sklearn should have been stated up front

The course felt like an advertisement for the professor's toolkit

It was very disappointing that the equivalent standard workflow was not supported

The instructors need to specify that you can run this course specialization using MAC or Linux only. I have wasted my time for the past 3 weeks trying to figure out how to run the Sframe or Turi using windows and could not find any solution.

The instructions to download GraphLab don't work and even when you sign to use the AWS platform the instructions are also old and I haven't been able to start any of the assignments because of that! I want MY MONEY BACK!!!

Shame that it was not possible to progress with this course without using graphlab which the creator of this course himself created. Please see the course as just a training sales promotion for his ML application.

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....

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.

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.

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.

The whole course based on some proprietary software. In general, it seems that the main goal of the course is promote that software.

there is no proper documentation.

at least there should be some clear instructions for first program

I dont like the tools they used, it seems like a promotion for their company.

Not made for Windows, you need a linux or mac VM to apply this course.

Complete waste of time until it is written using open-source packages.

Would have greatly preferred if open source tools were used.

I felt that I paid for demo of the Dato/Turi.

Not good support to learning process.

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.

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.

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!

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

Great course. Very informative and inspirational. I got tons of ideas from it! Thank you

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.

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 .

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.