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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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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

The course is good.Unfortunately once you have given the test it is closed and you cannot access any of your code and work

por Idris

21 de sep. de 2020

It is a good class for an intermediate level

por Steven M

10 de mar. de 2021

Guided project had an unrecoverable bug, and I could not complete it. After receiving no response from support, I just dropped the course.

por Aafreen

14 de oct. de 2020

I especially liked how the instructor made us understand what we were doing before we started and how after every task, he didn't forget to assign some extra exploratory work you could do in that task. These are not something most of the instructors do and I am speaking from experience. The project was well structured and I couldn't have asked for more

por Marwa A E

3 de ago. de 2020

Introduced to me the concept of SMOTE and how to use it for imbalanced datasets. Seeing, the effect of it on the datasets manipulated predicted results also showed how this technique makes classification problems more accurate.

por Hayan M

16 de oct. de 2021

I highly recommend this course due to the importance of its content, and the clear guidance. the the methods presented and explained in this course helps solving the real world problem much effectivly .

por Abekah C K

5 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

por Vaibhav T

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.

por Luis Á T M

24 de sep. de 2020

I really enjoyed it! Complete pipeline, really easy to understand. And there is a reference to the original dataset, that's really important

por Neha G

25 de ago. de 2020

Amazing course!! Thanks to the teacher for making contents easy to understand and incur the knowledge....

por Solomon T

3 de ago. de 2021

Practical content, very well explained.

por Divyanshu M

25 de ago. de 2020

Great learning experience

por Evgeni N

22 de mar. de 2022

Super useful!

por Jesus M Z F

1 de ago. de 2020

Great course

por Matta A A S

25 de ene. de 2021

good

por Merve D

29 de sep. de 2020

It is too easy. There is no missing data in the dataset, parameter tuning, outlier data, etc. It could be good for beginners.

por Hannah P

22 de ene. de 2021

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