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学生对 Coursera Project Network 提供的 Handling Imbalanced Data Classification Problems 的评价和反馈

54 个评分


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....



Dec 4, 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


Aug 16, 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.


1 - Handling Imbalanced Data Classification Problems 的 17 个评论(共 17 个)

创建者 Monika K

Jul 29, 2021

创建者 Idris

Sep 21, 2020

创建者 Steven M

Mar 10, 2021

创建者 Aafreen

Oct 14, 2020

创建者 Marwa A E

Aug 3, 2020

创建者 Hayan M

Oct 16, 2021

创建者 Abekah C K

Dec 5, 2020

创建者 Vaibhav T

Aug 16, 2020

创建者 Luis Á T M

Sep 24, 2020

创建者 Neha G

Aug 25, 2020

创建者 Solomon T

Aug 3, 2021

创建者 Divyanshu M

Aug 25, 2020

创建者 Evgeni N

Mar 22, 2022

创建者 Jesus M Z F

Aug 1, 2020

创建者 Matta A A S

Jan 25, 2021

创建者 Merve D

Sep 29, 2020

创建者 Hannah P

Jan 22, 2021