The complete supply chain data science handbook as Jupyter notebooks
- Updated
Mar 25, 2026 - Jupyter Notebook
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
19 Lessons - Master AI for Supply Chain Management from fundamentals to production
Build supply chain optimization models from zero - pure implementation step by step
My GitHub profile — Founder & CEO @Quantisage | AI + Supply Chain + Climate Tech
Activity-Based Costing for manufacturing — Kaplan & Cooper
AI demand orchestrator for unified demand planning across channels
Freight market rate analysis with lane-level benchmarking
SC scenario modeling with Monte Carlo uncertainty quantification
Min-cost network flow supply chain
Inventory risk pooling consolidation simulator
Supplier evaluation using Analytic Hierarchy Process
E-commerce order fulfillment center discrete-event simulation
Enterprise integration connectors for SAP, Oracle, NetSuite, Microsoft Dynamics, and other ERP/SCM systems with standardized APIs, data mapping, and real-time synchronization
Rough Cut Capacity Planning for SOP
Material Requirements Planning BOM explosion
Vehicle Routing Problem solver with savings algorithm
Real-time IoT data ingestion and streaming pipeline for Scope 3 carbon accounting using Apache Kafka, Spark, and PostgreSQL
EU Carbon Border Adjustment Mechanism (CBAM) calculation and reporting engine
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