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

4.5
étoiles
3,090 évaluations
586 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

MR
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

AD
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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101 - 125 sur 576 Avis pour Apprentissage mechanique pratique

par Nathan M

11 juin 2016

Extremely useful class! Jeff also has many excellent suggestions for resources that will teach you even more about machine learning.

par Diandian Y

28 nov. 2019

a broad coverage of content and very intuitive explanation for different algorithm. Good start point to learn machine learning.

par Avizit C A

30 janv. 2019

A very good course giving brief descriptions and applications of some of the used statistical and machine learning algorithms.

par Dan K H

27 mars 2017

Yet again an excellent course by Jeff, Roger and Brian. Thank you very much for a well layout course and some good excersizes.

par Peter D

7 oct. 2016

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

par andy p

9 août 2016

Great topic with a great instructor. Only wish the program was a little longer to spend some more time on some of the models.

par Prakhar P

6 juin 2018

This course introduces to the machine learning package caret. A solid launch pad into the exciting world of data analytics.

par Moisés E A

16 janv. 2017

Very good overview and straightforward explanations of the different methodologies of ML. Nice tips on how to do ML with R.

par Daniiar B

29 sept. 2018

It lucks theory, but that's why it's called practical. Very hands on teaching method. Was a little bit hard to follow.

par Sabitabrata M

10 juin 2018

Good course. Good overview on Machine Learning. But to understand the concepts I had to consult external resources.

par Robert K

26 sept. 2017

A great introduction to machine learning and it does a good job building on the material from the previous classes.

par Pam M

19 mai 2016

Good material, presented in an organized fashion. I was able to apply what I learned immediately in a work setting.

par Rahimullah S

28 oct. 2018

thank you, this class is very practical and informative. The projects are a little complicated but very practical.

par BOUZENNOUNE Z E

18 déc. 2019

A Great course that should be taken along other books, tutorials, and papers, in order to get the most out of it.

par Matthew S

8 mai 2019

Good introduction to machine learning. Provides pretty comprehensive coverage of major algorithms and approaches.

par Samir G

8 janv. 2017

Excellent course, very practical !

I am very curious about the maths so I will add some specialized certifications

par Jay S

27 août 2016

Excellent introductory course to Machine Learning. Very informative materials. Prof. Leek is a great teacher.

par Billy J

13 avr. 2016

Excellent introduction to machine learning. I feel that I have a good basic foundation to start building upon.

par MUZAFFAR B H -

15 oct. 2017

Essential starter for budding data scientist. Learned the basics and at least have the idea on how to conduct.

par Douglas M

1 févr. 2016

Great practical whirlwind tour. Light on theory, however, but it's a good entry point to the field. Thumbs up!

par benjamin s

9 juil. 2018

Probably the most enjoyable course of the specialisation, more maths would improve the quality of the content

par Philippine R

22 mai 2017

I learned so much in such a short period of time. Challenging, very hands on, great theoretical foundations!

par asma m

2 oct. 2018

The professor has a very clear lecture, brief and persistent comparing to others. I just love this course .

par Michael H

21 nov. 2020

Excellent breadth; only major issues have to do with Github challenges related to rendering HTML properly.

par Mehtab

24 août 2020

this course is just awsome, with some basic knowledge of data manipulation anyone would enjoy this course.