Scalable and user friendly neural 🧠 forecasting algorithms.

PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.

Zero-config time series forecasting for Python. 30+ models, auto selection, Forecast DNA, Rust turbo — one line of code.

A commercial AI-driven platform for real-time and end-of-day forecasting of all Tehran Stock Exchange symbols. Built in collaboration with industry partners and academic advisors, it integrates automated data-ingestion pipelines, deep-learning LSTM models, smart feature extraction (technical data & news data), and rolling 40-minute predictions.

Implementing 17 Machine Learning Models in a Hierarchical Data Architecture and Evaluating Their Performance

End-to-end demand planning — 6-model routing ensemble (MAPE 10.3%), capacity planning, demand sensing, S&OP simulation | MinTrace hierarchy, walk-forward CV, conformal prediction | Enterprise: K8s + Helm + Terraform + MLflow + Prometheus/Grafana | 192 tests

Multi-horizon demand forecasting system for retail inventory with hierarchical reconciliation, probabilistic predictions, and gradient boosting ensemble