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

3,168 évaluations
607 avis

À propos du cours

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

Meilleurs avis

13 août 2020

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

28 févr. 2017

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.

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526 - 550 sur 598 Avis pour Apprentissage mechanique pratique

par Léa F

9 janv. 2018

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

19 mai 2017

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

12 déc. 2017

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

9 mai 2018

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

8 août 2019

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

19 juil. 2016

Good course for learning the basics of the caret package. However, it is not a good course for learning machine learning.

par Joseph I

1 févr. 2020

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

5 févr. 2017

Superfluous but the existence of the package "caret" covers the gap of other libraries like "skilearn" of python


1 mars 2017

Instructor rushes the course and does not explain much in the same level of details as respective quiz requires

par Hongzhi Z

2 janv. 2018

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

13 oct. 2016

Exercises could be more complete, and some are outdated for latest R, giving slightly different results.

par Alex F

29 déc. 2018

A fine introduction, but there are much more engaging and better quality courses out there...

par Yingnan X

11 févr. 2016

If you have taken Andrew Ng's machine learning class, it's not necessary to take this one.

par yohan A H

6 sept. 2019

I think it was a very fast course and I feel more real examples would have been useful,

par fabio a a l l

14 nov. 2017

Poor supporting material in a course that tries to cover a lot in a very limited time.

par Rafael S

24 juil. 2018

this course seemed too rushed for me, too little content for such a extense subject

par Raj V J

24 janv. 2016

more needs to be taught in class. what is taught is not sufficient for quizzes.

par Surjya P

2 juil. 2017

Overally course is good. But weekly programming assignments will be great.

par 王也

17 déc. 2016

Too different for beginners but not deep enough for ones already know R.

par James F

10 sept. 2016

Quizzes are useful exercises but need to do a lot of self studying.

par Philip A

26 févr. 2017

mentorship was great, but the video lectures were almost useless.

par Christoph G

4 déc. 2016

The topic is too big, for one course from my point of view.

par Ariel S G

27 juin 2017

In my opinion, this course needs a few extra exercises.

par Jorge L

13 oct. 2016

Fair but assignments are not very well explained

par Bahaa A

20 oct. 2016

Good enough to open up mind of researcher