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Confidential Client
ML Production Platform — Forecasting, Recommendations & NLP Classification
A large food delivery platform operating across 20+ cities required a production-grade ML platform to improve operational efficiency through forecasting, personalised recommendations, and automated product classification.
Business Challenge
The client operated a high-volume food delivery platform and needed ML models in production — not just prototypes. Requirements spanned forecasting, product intelligence, and recommendations, all deployed and monitored at scale across multiple geographic markets.
Key Features
Preparation time forecasting using xgBoost and Deep Neural Networks for real-time ETA accuracy.
Order volume forecasting across 20+ cities using Facebook Prophet with COVID and weather external regressors.
NLP-based product classification at scale — 200k+ SKUs categorised automatically.
Recommendation systems using TF-IDF, collaborative filtering, and user clustering.
Full ML lifecycle: model training, evaluation, deployment, and automated retraining pipelines.
REST API delivery via FastAPI and Spring Boot for operational system integration.
CI/CD for ML models with automated testing and rollback capabilities.
Results
Production-grade ML covering forecasting, recommendations, and NLP classification across 20+ city markets.
ETA accuracy improved significantly, directly impacting customer satisfaction scores.
Automated classification of 200k+ products eliminated manual taxonomy maintenance.
Personalised recommendations increased order conversion metrics.
Tech Stack
xgBoost
Facebook Prophet
TF-IDF
Collaborative Filtering