$$ \text{Recommendation} = f(\text{User Embedding}, \text{Movie Embedding}) $$ Combine content-based filtering (CBF) with collaborative filtering (CF) for a hybrid model that leverages both movie features and user interactions. Download Geetanjali Font Instant
$$ \text{Recommendation Score} = \sigma(W_1[\text{User Embedding}] + W_2[\text{Movie Embedding}] + b) $$ Jana Czech Streets Review
$$ \text{Hybrid Recommendation} = f(\text{CBF}(\text{Movie Features}), \text{CF}(\text{User Interactions})) $$ A basic example could involve a neural network that takes in user and movie features to output a recommendation score: