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A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.

v1.2.0

3 months ago

What's Changed

  • More templates for causal inference: Evaluate data feasibility more accurately and efficiently by checking causal effects in data related to marketing campaigns, customer interactions, and price setting.
  • More prototypes for LLM-powered use cases: Prototype GenAI solutions for applied use cases such as data cleanings or system integration faster.
  • Readiness assessment and requirement gathering questionnaires: Expedite project scoping, identify risks sooner, and avoid overlooking important requirements and readiness gaps.

v1.1.0

4 months ago

What's Changed

  • Search - product attribute extraction, text-to-SQL, RAG
  • Demand forecasting - EST, ARIMA, DeepAR,

v1.0.0

4 months ago

What's Changed

  • Price optimization notebooks - dynamic pricing, bayesian models, unconstraining
  • Promotions and ads - propensity scoring using deep learning, dynamic personalization
  • Product recommendations - deep and hybrid recommenders, customer/item2vec
  • Search - visual search
  • Supply chain - single-echelon simulator, inventory allocation
  • Smart manufacturing - anomaly detection in metrics, images

v0.1.0

4 months ago

What's Changed

  • Price optimization notebooks - initial set
  • Promotion and ads optimization notebooks - initial set
  • Product recommendations - basic examples
  • Search - LSA example
  • Supply chain - RL-based prototype