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This lecture was delivered by Dr. Ramya Riya at Ankit Institute of Technology and Science. This lecture is part of lecture series on Machine Learning and Artificial Intelligence course. It includes: Recommender, System, Problem, Formulation, Predicting, Movie, Ratings, Content-based, Feature, vector, Optimization, Objective, Gradient, Descent
Typology: Slides
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= no. users = no. movies = 1 if user has rated movie = ra4ng given by user to movie (defined only if )
Movie Alice (1) Bob (2) Carol (3) Dave (4) (romance) (ac/on) Love at last 5 5 0 0 0.9 0 Romance forever 5?? 0 1.0 0. Cute puppies of love? 4 0? 0.99 0 Nonstop car chases 0 0 5 4 0.1 1. Swords vs. karate 0 0 5? 0 0.
Problem mo/va/on Movie Alice (1) Bob (2) Carol (3) Dave (4) (romance) (ac/on) Love at last 5 5 0 0?? Romance forever 5?? 0?? Cute puppies of love
Nonstop car chases
Swords vs. karate 0 0 5???
Op/miza/on algorithm Given , to learn : Given , to learn :
Given , es4mate : Given , es4mate : Minimizing and simultaneously:
Movie Alice (1) Bob (2) Carol (3) Dave (4) Love at last 5 5 0 0 Romance forever 5?? 0 Cute puppies of love
Nonstop car chases
Swords vs. karate 0 0 5?