• Welcome to the Extreme Challenges in Machine Learning!

• In this project, you will demonstrate what you have learned in this course by conducting an experiment dealing with Credits dataset.

• 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.