recommenders and Reco-papers
A comprehensive software library for building and evaluating recommendation systems complements a curated collection of foundational research papers, as practitioners typically implement algorithms informed by the academic literature.
About recommenders
recommenders-team/recommenders
Best Practices on Recommendation Systems
This project helps businesses and researchers build, test, and deploy systems that suggest products, content, or services to users. It takes in historical user interaction data and outputs personalized recommendations, which can be integrated into websites, apps, or internal tools. Anyone involved in enhancing user experience through tailored suggestions, such as e-commerce managers, content strategists, or product owners, would find this useful.
About Reco-papers
wzhe06/Reco-papers
Classic papers and resources on recommendation
This collection helps you understand and implement recommendation systems by providing a curated list of classic and modern research papers. You'll find materials covering various techniques for generating and ranking personalized suggestions. It's designed for data scientists, machine learning engineers, and researchers working on building or improving recommendation engines for products, content, or services.
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