recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course
Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.
par Brian F•
There was some good material in here, but it was rushed and is deserving of a much longer course - especially compared to some of the other modules in this course.
par Chuxing C•
the lack of assisted practices made it harder to digest the contents and methodologies.
strongly suggest to develop some practice problems with explanations.
par Michalis F•
Good in introducing caret package and getting some experience in running algorithms. Was expecting more in-depth discussion about the methods though.
par Davin G•
It's an excellent crash course to machine learning but the stats part was rushed. Had to look up external resources to understand what was going on.
par Léa F•
Rather good overview. The contents could dig deeper into each subject, and it would improve the course a lot if some exercises in Swirl were added.
par Miguel J d S P•
I didn't enjoy the supporting materials and the quizzes weren't very interesting. The final project was fine.
The subject is super interesting.
par Max M•
Should have gone into more depth and included swirl lessons, like previous courses. The quizzes were very challenging though, so that helped.
par Kyle H•
A brisk introduction to some of the basics of Machine Learning. Will leave with an understanding of a few ways to use the caret package.
par Manuel E•
Good course, but either explanations are too fast paced for the level of difficulty, or my neurons have began to decay with age.
par Noelia O F•
Good course for learning the basics of the caret package. However, it is not a good course for learning machine learning.
par Joseph I•
Material was very interesting but was covered at a very high level and a lot of additional learning was required.
par José A G R•
Superfluous but the existence of the package "caret" covers the gap of other libraries like "skilearn" of python
par BAUYRJAN J•
Instructor rushes the course and does not explain much in the same level of details as respective quiz requires
par Hongzhi Z•
All the formulas and code in slides are too abstract. If can be more charts to interpret that will be better.
par Henrique C A•
Exercises could be more complete, and some are outdated for latest R, giving slightly different results.
par Alex F•
A fine introduction, but there are much more engaging and better quality courses out there...
par Yingnan X•
If you have taken Andrew Ng's machine learning class, it's not necessary to take this one.
par Yohan A H•
I think it was a very fast course and I feel more real examples would have been useful,
par fabio a a l l•
Poor supporting material in a course that tries to cover a lot in a very limited time.
par Rafael S•
this course seemed too rushed for me, too little content for such a extense subject
par Raj V J•
more needs to be taught in class. what is taught is not sufficient for quizzes.
par Surjya N P•
Overally course is good. But weekly programming assignments will be great.
Too different for beginners but not deep enough for ones already know R.
Quizzes are useful exercises but need to do a lot of self studying.
par Philip A•
mentorship was great, but the video lectures were almost useless.