nikhilpereira24/Recommendation-Systems-Algorithmic-Pricing

Developed predictive ratings to craft personalized recommendation systems with matrix factorization. Dealt with real-world implications: cold start/missing data, capacity constraints and matching in 2-sided marketplaces. Priced under uncertainty by estimating demand using dynamic programming for over-time pricing problems. Worked with data and deployed decision-making models in socio-technical systems; handling user incentives and strategic behavior, networked and decentralized decision-making, and feedback loops between deployed models and future data.

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