Abstract
This Study discusses the development of an intelligent operating system feature that supports smart prediction and recommendations using artificial intelligence (AI) capabilities within the Linux operating system. The study aims to integrate AI-driven features into Linux to enhance user productivity and efficiency by providing relevant application recommendations based on user behavior patterns. The implementation involves data collection of application usage, training machine learning models for application recommendations, and integrating these features into the Linux environment. The project utilizes Python for scripting, employing libraries such as psutil, pandas, scikit-learn, and joblib for data handling and machine learning tasks. The results demonstrate successful implementation of the AI-driven recommendation system, enhancing user interaction and productivity within the Linux operating system
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