Svd.
recommendations. By decomposing a user-item interaction matrix, SVD can identify latent factors or patterns that capture users’ preferences and item characteristics, enabling accurate recommendations. Principal Component Analysis (PCA): PCA is a statistical technique that utilizes SVD to find the