Great course to get started on the ML journey. I had some initial difficulty in setting up the environments and manage the various package dependencies. But once it was set up then the rest of the course was really enjoyable and enriching.

It is a nice course for me to review some data science concept and learn a little about deep learning. The use of Graphlab is a little annoying considering rarely any companies use it but the code used is easy to understand for beginners.

Good introduction to machine learning concepts and I'm looking forward to a deeper dive in later courses. Would have preferred the course use industry standard, open source tools, but GraphLabs/SFrames didn't cause an issue for me at all.

Very well driven by the lecturers. Very good overview. My only concern is the difficulity in setting up the working environemnt for python.: I needed to solver serveral issues not mentioned in the guidelines, which took me several hours.

Thoroughly enjoyed the case-study approach toward learning fundamental machine learning concepts. The abstraction level is a great match for professionals who are beginning to understand key machine learning concepts beyond buzz-words.

Great course! I had to watch some of the videos over and over again for the material to really sink in but after I understood what's happening it was very enlightening. This course will really get you hooked into learning data science!

Very good introduction to machine learning. Concepts are well presented and explained, i would have preferred to use a Open Source library in the assignments, but is not bad to know how to use Graphlab, a very powerful tool, for sure!

Lab work instructions are not well written, it is taking lots of time to understand what we are trying to do. Next thing is we need to know the right answers after certain threshold so that we can understand where we are doing wrong.

Very good approach to this topic. Very good explanation even of complex subjects. It is a general overview and allow the student to have a basic knowledge of all machine learnings sub-topics. Maybe to depended on dato dato framework.

It's a practical approach to different machine learning techniques, it would be great not to depend a lot of DATO, but I think at the other hand that dependency allows to focus in machine learning than in program things with python.

Best way of teaching such peculiar concepts with so ease using the best live examples . Great sessions and great energy of Carlos and Emily made it cool and much more simpler to learn . Had a great learning experience with them .

Course is pretty well designed, I like how practical it is and the case study approach. It's a great introduction course to ML. One suggestion I have is to make it easier to use Sklearn and panda which are more popular in industry

First of all - you are both excellent teachers and concepts were very well explained at this foundation level. My only doubt was how current the content is given that ML and AI are evolving so much everyday. Otherwise - great job!

The course its a pretty good introduction to machine learning, we explored different technics, models and alghoritms. Im very pleased of what I learned in this course. 4 Stars because some explications needs a little more detail.

Could have explained a little more about what we were doing for some of the modules. For example, in week 6, I didn't really understand the 'deep_features' column or how the values for that column were generated for each picture.

I have just completed the course.I have got an overview of how machine learning works.What I felt is that the course is a very good one for the beginners in ML.

PS: Increase the toughness and level of the questions in the quiz

Awesome module, but the Deep Learning course should be redone in my honest opinion. The explanation for it is on way too high of a level compared to the other courses within this module and way too bogged down in the details.

It is a very awesome course but I am giving it a 4 star because I enrolled in it, without knowing that it is using Turicreate and teaching graphlab but in real life, there is barely any company which uses these two libraries

I think the text of the programming assignments could be improved. The minimum that should be done, I think, is to do some serious proofreading. I found a lot of mistakes in language (and English is not my native language).

It'd have been better if at least one of the case studies started with raw data. The steps to get raw data to Graphlab/SFrame understandable form are not covered and I think it is important. Otherwise an excellent course.

Thank you very much for the course. I have developed my algorithm on Matlab environment, so far. I have introduced to Python with the help of the course and have obtained much crucial information about machine learning.

Great course for beginners in machine learning.It has created a lot of interest in the field and looking with great expectations for the upcoming implementation courses for the inbuilt functions we used in this course.

Really good foundation for understanding Machine Learning and how to apply the specific methods. The approach of utilizing use cases makes it easier for the user to paint the picture and understand the business problem

It was overview of things that one does using ML. The instructors focused just on the concepts, leaving the internal working on algorithms and that helps someone is very new to this field to first get a broader picture

Nice course for fundamentals with good assignments which really make us work. Only bad thing is that the material was somewhat outdated and they haven't updated all the things like the quizzes with the new framework