Search Results for "recommendation"

...This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information.

mallThe project is an e-commerce system, including a front-end mall system and a back-end management system, implemented based on SpringBoot+MyBatis, and deployed with Docker containers. The front-end mall system includes homepage portal, product recommendation, product search, product display, shopping cart, order process, member center, customer service, help center and other modules. The background management system includes modules such as product management, order management, member management, promotion management, operation management, content management, statistical reports, financial management, authority management, and settings.

Seldon Server is a machine learning platform and recommendation engine built on Kubernetes. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production.

easyrec is a recommender system that aims for easy integration of recommendations into web applications. It has a web based admin tool, and its recommendation engine is accessible through a REST API, providing methods like 'other users also bought'

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.