👉 Recommendation engineering is the process of developing algorithms and models to suggest items, such as products, movies, or articles, to users based on their preferences and behavior. It leverages data from various sources, including user interactions, item attributes, and contextual information, to predict what users might find relevant or desirable. The core of recommendation engineering involves techniques like collaborative filtering, content-based filtering, and hybrid approaches, which can be further enhanced by machine learning methods such as deep learning. The goal is to personalize user experiences, increase engagement, and drive conversions by providing tailored suggestions that align with individual tastes and needs.
