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Welcome to the Extreme Challenges in Machine Learning!
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In this project, you will demonstrate what you have learned in this course by conducting an experiment dealing with Credits dataset.
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We have seen in the lectures what are the challenges needs to face in case of the data is imbalanced.
- What is Imbalanced Data
- Dealing with imbalanced data
- Evaluation Metrics
- Resampling Techniques
- Algorithmic Techniques
- Dealing with small datasets
- Values of K in K-Fold validation
- Do we need hundreds of classifiers?
- So in this exercise You are given a data set. Use your Machine learning skills to solve it.
- Yes! you are correct use whatever you feel like to solve these exercise and get the best AUC score.
- These exercise will be good kick start for your future Hackerthon competition.
- You will be learning how to handle dataset from start to end.
To perform these excerise we will use Credits
dataset from ISLR library.
This dataset contains following features:
- Income
- Limit
- Rating
- Cards
- Age
- Education
- Gender
- Married
- Ethnicity
- Balance
Target Variable:
- Student
Details information is mentioned in task.