Avis et commentaires pour d'étudiants pour Apprentissage mechanique pratique par Université Johns-Hopkins

It's harder than the previous one. it would be nice to update some the quizzes as they are based on older versions of R Studio libraies.

The quiz should be constructed in a way that depends less on the version of the libraries used. The rest of course was excellent.

Vary practical approach, almost no theory or in-depth explanation of the subject, but a lot of focus on applying ML in practice

To me with this course, the best learning aspect is the final project; how to use Machine Learning Algorithms on data analysis.

Good course, some aspects of the assignment were a bit beyond the scope of what the course teaches but overall I learnt a lot.

Was pretty good, but quite short and some assignments did not align as well with the lecture material as they could have.

This is a great course, but it would be good to see it updated to use the newer evolution of the caret package, parsnip.

Very good course. I am very knew to this topic but am sure will find a lot of application in my speciality - geophysics

Good introduction to machine learning, might suffer a bit from trying to cover too much ground in such a short time.

I hope we can have more détails in this cours and to see how to use the algorithms for the big data. Thank you.

I enjoyed it but it needs indeed to deep into many concepts, which are just briefly named during the course.

Great course, very demanding, but it could use more reading material, ebooks instead of links on video.

Good overview of available techniques and the Caret package. Will get you started in machine learning.

This was a superb module which created a deep learning insight within me focusing on future technology

Got confused how to perform cross validation and when. Other than that, very practical. Great job.

The course is really great, however it should last a little longer, 4 weeks is hard to accomplish

Very interesting course. May be a little bit harder than the previous ones but it could be done.

Good course, I learnt a lot. It does need to be updated with more modern versions of software.

Very quick overview. If you really want to know something about it read the reference books.

Title says everything. Practically and basically no theory explained. Good course though.

Excellent content so I give 4 starts. I stat less because the trainer speaks too fast.

I thought there were Swirl practice as other courses, however this course is very good.

Great Course, will be nice to have more projects to see how it goes with different data

good course for initial understanding of machine learning. SVM can also be included.

I learned a lot in this course, but I would recommend taking the courses in order.