👉 Recommendations engineering is a specialized field within data science and machine learning focused on designing and implementing systems that provide personalized recommendations to users. It involves collecting and analyzing user data, such as browsing history, purchase patterns, and preferences, to build predictive models that suggest relevant items or content. The process typically includes data preprocessing, feature engineering, model selection (often leveraging collaborative filtering, content-based filtering, or hybrid approaches), and continuous evaluation to ensure recommendations remain accurate and relevant. Effective recommendations engineering aims to enhance user experience, increase engagement, and drive business outcomes by delivering tailored suggestions that align with individual user needs and preferences.
