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

4.5
étoiles
3,175 évaluations
610 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 601 Avis pour Apprentissage mechanique pratique

par Chris N

7 juin 2017

loved it - fascinating subject and more detail than you could possibly want from the course instructors. Friendly community in the forum too.

par Matthew W

1 mars 2016

High level and brief overview but found it informative introduction into machine learning with R. The final project is fun and interesting.

par Javier A D

27 mai 2018

References were very usefull for doing deep analisys in the thems

Quices were challenge.I learn a lot solving them.

I mis the swirl sessions

par מיקי כ

15 juil. 2021

Although I had no knowledge on the subject, the instructor presented it in such a clear way, that I understood it completely by few weeks.

par Swaraj M

5 mai 2020

Thank you coursera for helping to get the fundamentals of machine learning, now I am confident enough to switch my career in data science.

par Laro N P

22 juil. 2018

Good course, I miss more practice exercise because theory is always welcome but when we are capable to understand is doing real practice.

par Sanjay J

6 oct. 2020

Fantastic course, and loved the hand's on projects and assignments. Good course to practically get started in machine learning using 'R'

par Gustavo S

19 avr. 2020

Very nice course, well-explained, sometimes a little bit fast if you dont have the luck of having previous knowledge.

100% recommendable

par Jay Y

17 nov. 2021

Thank you very much for offering this course, and for going to extraordinary lengths to help us understand the concepts and use models

par Susan M

10 déc. 2020

Excellent instruction followed up with projects to enable thorough understanding as well as ability to use the data science skillset.

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 Dan 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 manuel s g

27 avr. 2021

I learn a lot on this one. Always complex when it is a long time since last maths studies and university eneded ;-)

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.