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Voltar para Aprendizagem Automática na Prática

Comentários e feedback de alunos de Aprendizagem Automática na Prática da instituição Universidade Johns Hopkins

4.5
estrelas
3,199 classificações

Sobre o curso

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....

Melhores avaliações

JC

16 de jan de 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

13 de ago de 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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151 — 175 de 606 Avaliações para o Aprendizagem Automática na Prática

por Enrique A M

18 de out de 2020

Mil Gracias Maestro Roger y demas docentes, Mil gracias U. John Hopkins, Mil Gracias Coursera.

por Gustavo C G

7 de ago de 2019

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

por Thodoris M

10 de jul de 2018

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

por Wesley E

15 de fev de 2016

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

por André C L

13 de dez de 2018

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

por Raunak S

19 de nov de 2018

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

por Tristan F

25 de dez de 2019

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

por Oleksandr K

11 de jul de 2018

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

por Jean N

24 de ago de 2017

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

por Tomer E

6 de ago de 2020

Great course!

Covers basics of machine learning algorithms and how to implement them in R.

por Rizwan M

13 de out de 2019

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

por Connor B

24 de set de 2019

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

por Alfonso R R

13 de nov de 2018

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

por Brian G

17 de ago de 2017

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

por Paresh P

8 de dez de 2020

Explained practical machine learning well, concepts like model stacking really helped!

por Sean D

10 de jun de 2020

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

por Konstantin

2 de mar de 2020

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

por Donson Y

4 de set de 2017

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

por Jorge A

13 de abr de 2016

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

por Premkumar S

16 de mar de 2019

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

por Sai S

17 de jul de 2017

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

por Thet P S A

21 de ago de 2020

It supports a lot in my thesis. Thank you, lecturers, at John Hopkins University.

por Mary

19 de ago de 2019

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

por Nikhilesh J

2 de mar de 2018

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

por Jeffrey M H

10 de jun de 2019

So far, one of the most fulfilling courses in the Data Science specialization!