Editor’s Note: The SCM thesis Reducing Oil Well Downtime with a Machine Learning Recommender System was authored by Jesús Madrid and Andrew Min and supervised by Dr. Cansu Tayaksi ([email protected]).

SAN FRANCISCO--(BUSINESS WIRE)--Rubber Ducky Labs, a company dedicated to making recommender systems easier to build and imbue with human knowledge, today announces $1.5 million seed investment round ...

Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items to be a barrier to using the ...

apply (recsys) focuses on the specific challenges of building recommender systems and will cover best practice development patterns, tools of choice and emerging architectures to successfully build ...