v1.2.0

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

What's Changed

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

v1.0.0

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

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