sarath sriram A

Explaining how predictive models forecast churn risk and future revenue for telecom operators.

Describing techniques to identify at‑risk customers and calculate their lifetime value.

Discussing best practices for creating interactive dashboards with Power BI.

Detailing construction of Python ETL pipelines that clean data and load into PostgreSQL.

Reviewing model choices like XGBoost for classification and Random Forest for regression.

Outlining deployment of FastAPI services within Docker Compose for real‑time scoring.