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Avis et commentaires pour l'étudiant pour Apprentissage mechanique pratique par Université Johns-Hopkins

4.5
2,671 notes
500 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!

AD

Mar 01, 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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126 - 150 sur 491 Examens pour Apprentissage mechanique pratique

par YOGESH C

Jun 18, 2016

great course

par Artem A

Apr 14, 2016

Noiiice!

par Sindre F

Aug 01, 2016

A good introduction to machine learning.

par Rafael L G

Jun 09, 2017

N i c e

par Brian G

Aug 17, 2017

Great course. Mechanics of the final assignment are more difficult than the work itself.

par Gustavo E L

Mar 14, 2016

With this course, you can develop an important skill for the final steps of a data science project.

par Sebastian R

Sep 19, 2017

Great intro machine learning, you will know how to use it

par Krishna P

Jun 20, 2016

Very good content for beginner, lot of learning in machine learning special caret package in R.

par HARSH L

Jul 11, 2016

Awesome course giving a practical experience of a Data Scientist.

Perfect place to get your hands dirty! :)

par Samuel H

Feb 18, 2016

This was a very good introduction to machine learning and how to use machine learning packages in R. It would have been better if the class had been longer than four weeks, but I learned a lot for the length of the course.

par Paula L

Dec 02, 2016

good course, but one who is serious about data science should view this course as a starting point since machine learning is a semester long course so I'd recommend follow up with machine learning course taught from Andrew Ng out of Stanford

par Peter D

Oct 07, 2016

One of my favorites in the series! What I have been waiting for building up the prerequisite knowledge. Enjoy the instructor!

par Larry G

Feb 07, 2017

Nice

par Carlos M B B

Aug 10, 2017

This was one of the better courses in the series, thanks.

par 朱荣荣

Apr 26, 2016

good and useful!

par Chris H

May 23, 2016

Great course. I really enjoyed working on the prediction project at the end.

par Policarpio S

Mar 28, 2016

I really enjoyed this course. The material was concise and allows me to get up and running with ML.

par Mehdi Z

Mar 25, 2016

Hands-on training, practical introduction to machine learning using R!

par Felix A

Sep 20, 2016

Unexpectedly challenging and insightful.

par Dimitrios G

Jul 07, 2017

Amazing course. Short videos packed with information!

par Neven S

Jan 22, 2016

Very good!

par Xray W

Mar 21, 2016

Principle and practices. Good coverage on topics to get you started!

par Abhishek S

Aug 15, 2017

Excellent course.

par PATRICK

Mar 02, 2017

Nice, clear and concise.

par Roberto D

Jun 20, 2017

Methods to be applied in preparation for creating a data product.