Une très bonne introduction par la pratique aux différentes notions et concepts du Machine Learning, avec assez d'éléments concrets pour pouvoir commencer à mobiliser ces théories dans un contexte pratique.

+ Excellent video lectures.

+ Good overview of the field.

+ Nice working examples with good instruction video's.

-- No help with the practical assignments although the Python examples given are not flawless.

Four years ago, this course deserves a five-star review. But as the turicreate has changed a lot, some functions cannot be used and some error appears in the hand-on part. But, it is still pretty good.

The Course was very neatly presented, although we used lots of predefined functions to work around Machine Learning Algorithms it was good to know about the concepts that was thought extremely well.

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

Good for a introductory course if someone is getting started with machine learning, but as part of an specialization i think is useless (for people who are planning to take all the specialization).

Graphlab is used during the class, where as in assignments, turicreate is used. This causes slight variation in the results between the two. This may cause loss of points in the assignment.

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