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

4.5
étoiles
3,010 évaluations
572 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

JC

Jan 17, 2017

excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!

MR

Aug 14, 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

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376 - 400 sur 563 Avis pour Apprentissage mechanique pratique

par Igor H

Sep 10, 2016

Rather basic, nevertheless a good introduction to the topic of machine learning with R. Mostly concentrated on applications of the R caret package.

par Lee G

Sep 22, 2017

A very good starter course on Machine Learning in R with great links to various resources that students and delve deeper into the various topics.

par Yashaswi P

May 24, 2020

Good Course the covers a lot of practical aspects and relevant to the real world solution.

Good References and Learning Materails are available

par Ann B

Sep 06, 2017

Good class to get the basics of Practical Machine Learning. This course is best taken as a part of the data science series from John Hopkins.

par Hernan S

Dec 13, 2016

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

par Jakub W

Sep 24, 2018

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

par Md F A

Aug 14, 2017

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

par Rhys T

Oct 10, 2017

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

par Níck F

Sep 27, 2016

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

par Michael O D

Jan 10, 2020

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

par Tongesai K

Feb 08, 2016

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

par Kevin S

Mar 03, 2016

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

par Sulan L

Nov 19, 2018

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

par A. R C

Oct 20, 2017

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

par marcelo G

Aug 15, 2016

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

par Jeffrey E T

Mar 28, 2016

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

par BIBHUTI B P

Jul 24, 2017

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

par João R

Aug 20, 2017

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

par Daniel R

May 14, 2016

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

par César A C

Jul 26, 2018

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

par Greig R

Nov 14, 2017

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

par Pieter v d V

Jun 28, 2018

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

par Guilherme C

May 18, 2016

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

par Carlos C

Aug 12, 2017

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

par carlos j m r

Oct 05, 2017

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