5.Energy Consumption Forecasting Engine (Causal ML + Time-Series Modeling)

Time-Series Forecasting • Causal Inference • ML Systems 🔗 GitHub Repo

Developed forecasting engine using XGBoost, RF, Transformers, and Prophet to model consumption patterns for power companies.

Applied DoWhy for causal inference, revealing feature–consumption relationships to guide capacity planning.

Delivered end-to-end CRISP-DM pipeline translating raw time-series data into actionable predictions.

Why this is attractive to Netflix: Shows strong forecasting, causal ML, and modeling capabilities applicable to personalization, demand prediction, and content optimization.