Course contents are good - however the forums are not active and there is no follow up from faculty to update the course specialization following the change in course structure (eg. no capstone)

This course is very good. The only problem is that instead of using open source packages like scikit-learn they decided to based it on proprietary GraphLab (which is free only for academic use).

Good course, a tiles a litte coursory, but a decent introduction to the concepts and vocabulary of machine learning. Something like this should be required for anyone who works with data today.

Decent intro, though it would be a lot more useful if the professor didn't use his Software and instead thought us implementations using python/R which are used in most commercial applciations

It gives you a fair insight to the world of machine learning, without getting into much technical detail. I guess this information is saved for the next courses of the Machine Learning group.

it would be really great if you will teach the provided note book practice examples

and deep learning is a bit harder and faster

instead graphlab if you use sklearn module it would be amazing

This course provides a quick and easy introduction to machine learning and python. I enjoy the learning experience. The materials have room for improvement: there are typos and redundancies.

It is a good course indeed. I have enjoyed the notebook practical part most. Though the theoretical part is a bit boring, I have learnt a lot. Thank You for designing the course in such way

I like the introductory format of using case studies of a wide range of methods, it gives you an overview of the core machine learning algorithms that are used, and what they are used for.

Se deben actualizar algunos Notebooks, la librería de turicreate ha cambiado y algunas funcionalidades no están disponibles para python 3. Lo cual complica las respuestas en los examenes.

Many practical examples for usages of machine learning.

Almost concepts, no hard math works.

Recommend for beginners who interested in machine learning but did not have any math background.

The course is fantastic and presented well. I never got my feet under me because i had a lot going on at work. Does have some linear algebra pre-reqs that you can brush up @ khan acedemy.

Every topic is nicely explained in this course but the only problem is that I was unable to install graphlab library, so it would've been better if any other library would've been used.

It is a great course. Congratulations! Everything is subject of improvement, though. Check again that the version of graphlab referred to in the videos is the one available to download.

The instructors are excellent and the material is good. The only drawback is the need to use Graphlab. This would have been a really great course if we had to use open source software.

Wonderful Course that I have really enjoyed while learning understandings of Machine Learning and its applications in real-world problems. Thanks to Instructors and Coursera and Team

i understand the use of graphlab to make thinks easy... but it would be better to state that on the description of the course, because i don't see myself using graphlab in the future

I was blocked with the Turicreate and Sframe libraries because Turicreate doesn't install on windows (outside of a virtual machine). I'd prefer more standard libraries for training.

Great introduction course on Machine Learning. Got hands on experience to build Regression, classification, clustering, recommending & deep learning model with python and Graphlab.

I really like this course. Very nice introduction to ML. The only downside is that it would be nice to have some comments on how to implement the algorithms without using Graphlab

Very interesting and easy to learn course. But I'd like to more of mathematical background in algorythms and of course use open-source libraries instead of proprietary graphlab.

Very nicely compiled set of lectures: I am new to machine learning and am finding this course very conducive to understanding some key ML algorithms using a case-study approach.

The case study approach of this course makes it interesting and fun to learn the concepts of Machine Learning. I only wish more live examples were used to explain the concepts.

I think it is one of the best courses to start with in Machine Learning. It shows you the big picture and different problems that Machine Learning could be used in the problem.

excellent intro to the field for newbies. the only thing i would improve is that some of the coding concepts could have been explained more clearly and more practice exercises.