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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
3,200 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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601 — 607 de 607 Avaliações para o Aprendizagem Automática na Prática

por Eduardo S B

26 de jan de 2020

They explain nothing on the fundamentals of the machine-learning methods, nor how to know which method apply to a given problem.

por Abhilash R N

4 de dez de 2019

This course is NOT for the beginner. Take time to finish all the beginner and foundation courses and then take time to learn R

por Yesica B

29 de dez de 2021

I wanna know, what is happening with my grade with this course. I still wait long time ago. Please, help me.

por Emily S A

25 de mai de 2020

In my opiion, this course needs to be improved a lot. There are almost nothing Practical Machine Learning.

por yi s

19 de jul de 2016

too general no depth, not recommended for science or engineering degree holders

por Stephen E

27 de jun de 2016

To be honest I don't think this is worth the money.

por Stephane T

31 de jan de 2016

Too much surface, not enough depth.