- California Housing Price
- Customer Churn
The notebook consists of 3 Major sections
- Dataset info
- Identifying Attributes to be processed
- Pipeline Implementation using custom transformers
- The notebook consists of application of KMeans on dataset and adding a Cluster Column.
- The resulting cluster values are compared to that of churn.
- Correlation matrix is computer to analyze important features and how they affect Churn.