Large Language Model (LLM) Data | Machine Learning (ML) Data | AI Training Data (RAG) for 1M+ ...
收藏资源简介：
A comprehensive dataset covering over 1 million stores in the US and Canada, designed for training and optimizing retrieval-augmented generation (RAG) models and other AI/ML systems. This dataset includes highly detailed, structured information such as: Menus: Restaurant menus with item descriptions, categories, and modifiers. Inventory: Grocery and retail product availability, SKUs, and detailed attributes like sizes, flavors, and variations. Pricing: Real-time and historical pricing data for dynamic pricing strategies and recommendations. Availability: Real-time stock status and fulfillment details for grocery, restaurant, and retail items. Applications: Retrieval-Augmented Generation (RAG): Train AI models to retrieve and generate contextually relevant information. Search Optimization: Build advanced, accurate search and recommendation engines. Personalization: Enable personalized shopping, ordering, and discovery experiences in apps. Data-Driven Insights: Develop AI systems for pricing analysis, consumer behavior studies, and logistics optimization. This dataset empowers businesses in marketplaces, grocery apps, delivery services, and retail platforms to scale their AI solutions with precision and reliability.
