Chevron Left
Effectively Dealing with Imbalance Classes(으)로 돌아가기

Coursera Project Network의 Effectively Dealing with Imbalance Classes 학습자 리뷰 및 피드백

강좌 소개

In this 2 hour guided project you will learn how to deal with imbalance classification problems in a profound manner, applying several resampling strategies and visualizing the effects of resampling on imbalance classification dataset. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
필터링 기준:

Effectively Dealing with Imbalance Classes의 2개 리뷰 중 1~2

교육 기관: Mohammed K

2020년 11월 29일

Learnt lot of new technique for handling imbalanced dataset. Good project. However, I strongly recommend downloading the dataset from internet and run locally. Coursera's platform for running the project is confusing.....Overall good project.

교육 기관: Yaron K

2021년 8월 28일

Pro: Covers various techniques for handling imbalanced data sets. With metrics and visualizations

Con:

- Audio is sometimes hard to hear. However the closed captions help. - The Rhyme platform is problematic. Eventually I downloaded the dataset and ran the notebook locally. - The complete notebook isn't available. I think it is better when you have a complete notebook and can concentrate on listening to the lecturer and annotating the notebook.

Other: - There is no theory, just a demonstration of various techniques for under and over sampling. On the whole I think this is positive. There are a lot of techniques. So first find the one that is relevant to your data-set - and then study it further on the Internet. - It seems that there have been changes in the imblearn library so sm = SMOTE(), x_sm, y_sm = sm.fit_sample(X,Y) doesn't work. You need to change it to fit_resample().

Conclusion: Would definitely take another project given by the lecturer. Mainly because of the emphasis on visualizations and metrics. With so many examples on the internet - you'll always eventually have an ML that runs. The real challenge is ensuring the results are fit for use.