Releases · ikatsov/tensor-house

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.

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