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

4.5
étoiles
2,890 évaluations
547 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

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.

DH

Jun 18, 2018

Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.

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126 - 150 sur 539 Avis pour Apprentissage mechanique pratique

par Yadder A G

Oct 31, 2019

It's the best course I've taken. It has all the basics about machine learning algorithms and more.

par Yap Y A

Mar 11, 2019

Instructor was clear in his explanation. Would prefer to have more hands on exercise for practice

par Weiqun T

Sep 23, 2019

This is a very good basic course for machine learning. I got the basic ideas and skills for it.

par Сетдеков К Р

Feb 03, 2020

Great course! Very useful to train using advanced classification models and ensemble learning.

par Krishna P

Jun 20, 2016

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

par Gustavo C G

Aug 07, 2019

Excellent introduction to machine learning. Great examples and detailed explanations, as usual

par Theodoros M

Jul 10, 2018

Practical ML is a great course, that provides training in the practical aspects of the topic.

par Wesley E

Feb 15, 2016

Great introduction with a broad set of tools and plenty of resources for more in depth study.

par André C L

Dec 13, 2018

very good practical experience using machine learning models, especially regarding PCA usage

par Raunak S

Nov 19, 2018

a very good course for those wanting to learn Machine Learning to implement in Data Science.

par Tristan F

Dec 25, 2019

Lectures were very clear and helpful! Professor Leek was great at breaking down the topics.

par Oleksandr K

Jul 11, 2018

Great course! However, it would be good to learn about artificial neural networks as well.

par Jean N

Aug 24, 2017

Very nice Course. I am applying it right away for Predictions in the Telecoms environment.

par Rizwan M

Oct 13, 2019

great course. could have explained more techniques in caret package with coding examples

par Connor B

Sep 24, 2019

Really good exposure to machine learning and builds on the previous course in regression

par Alfonso R R

Nov 13, 2018

Hands on course. Loved it. It goes a little bit fast, however, the content is ambitious.

par Brian G

Aug 17, 2017

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

par Sean D

Jun 10, 2020

Really liked Dr. Leek's talks, and the subject matter was interesting and kind of fun.

par Konstantin

Mar 02, 2020

Excellent course. Lots of exorbitantly useful knowledge. I`ve been lucky to start it.

par Donson Y

Sep 04, 2017

This is a fantasy course to know that how to build your first machine learning model.

par Jorge M A A

Apr 13, 2016

I enjoyed a lot this module, I'll use at my daily work some of the features I learned

par Premkumar S

Mar 16, 2019

Great course and farily challenging exercises! Thank You for putting this together!!

par Sai S S

Jul 17, 2017

Great course. Ways to curb plagiarism & cheating needs to be revisited by your team.

par Mary

Aug 19, 2019

Very informational with good variety of code to take back and apply to projects.

par Nikhilesh J

Mar 02, 2018

Provides a quick and dirty look at Machine Learning. An easy way to get started.