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Opiniones y comentarios de aprendices correspondientes a Handling Imbalanced Data Classification Problems por parte de Coursera Project Network

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Acerca del Curso

In this 2-hour long project-based course on handling imbalanced data classification problems, you will learn to understand the business problem related we are trying to solve and and understand the dataset. You will also learn how to select best evaluation metric for imbalanced datasets and data resampling techniques like undersampling, oversampling and SMOTE before we use them for model building process. At the end of the course you will understand and learn how to implement ROC curve and adjust probability threshold to improve selected evaluation metric of the model. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Principales reseñas

AK

4 de dic. de 2020

This is an amazing project with nice explanations! If you are into credit scoring and things of that sort, I highly recommend it. I just wished he elaborated more how to detect the threshold values

VT

16 de ago. de 2020

Really amazing course. The basics of handling imbalance data are covered really well. Good explanation of how to work with ROC curve and get the right threshold to increase the target metrics.

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1 - 17 de 17 revisiones para Handling Imbalanced Data Classification Problems

por Monika K

29 de jul. de 2021

por Idris

21 de sep. de 2020

por Steven M

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por Aafreen

14 de oct. de 2020

por Marwa A E

3 de ago. de 2020

por Hayan M

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por Abekah C K

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por Vaibhav T

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por Luis Á T M

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por Solomon T

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por Divyanshu M

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por Evgeni N

22 de mar. de 2022

por Jesus M Z F

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por Matta A A S

25 de ene. de 2021

por Merve D

29 de sep. de 2020

por Hannah P

22 de ene. de 2021