Task 6

[bhadauria-harish]

Description

Description

• In this notebook I performs an analysis of credit card customer data. The workflow includes data exploration, cleaning, feature scaling, and clustering. Using unsupervised learning (primarily K-Means clustering).
• Part 2: I apply PCA on the Iris dataset to reduce its dimensionality and visualize the data in principal component space.
• Part 3: I work with the Digits dataset, applying PCA to reduce the number of features while retaining most of the data variance. I experiment with different numbers of components to find a sweet spot that balances dimensionality.

Notes for the reviewer

• How can we determine which cluster corresponds to which type of customer or payment behavior ? in Part 1
• I was unable to find the sweet spot that balances dimensionality and explained variance.