The complete supply chain data science handbook as Jupyter notebooks
49 production-ready Python recipes for supply chain management
12 Lessons - Build autonomous AI agents for supply chain planning procurement and logistics
Build supply chain optimization models from zero - pure implementation step by step
19 Lessons - Master AI for Supply Chain Management from fundamentals to production
My GitHub profile — Founder & CEO @Quantisage | AI + Supply Chain + Climate Tech
SC scenario modeling with Monte Carlo uncertainty quantification
Activity-Based Costing for manufacturing — Kaplan & Cooper
Min-cost network flow supply chain
Inventory risk pooling consolidation simulator
AI demand orchestrator for unified demand planning across channels
Freight market rate analysis with lane-level benchmarking
Supply chain risk quantification via Monte Carlo simulation
Supplier network graph analysis with centrality and vulnerability
Truck load planning mixed SKU shipments
Multi-tier supply chain visibility mapping and risk propagation analyzer
Warehouse slotting optimizer — De Koster et al. methodology
EU Carbon Border Adjustment Mechanism (CBAM) calculation and reporting engine
Real-time IoT data ingestion and streaming pipeline for Scope 3 carbon accounting using Apache Kafka, Spark, and PostgreSQL
Material Requirements Planning BOM explosion
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