Collaborative Filtering, Matrix Factorization, Recommender Systems, Gradient Descent, Neural Networks.
using the linear operation of matrix multiplication: # Create random initial latent matrices U = np.random.uniform(-1, 1, size=(num_users, K)) V = np.random.uniform(-1, 1, size=(num_items, K)) N = num_users * num_items # Training for curr_epoch in range(num_epochs): # Reconstruct R_hat from latent