In modern computing systems, efficient file management is crucial for enhancing productivity and enabling seamless access to information. For example, the increasing volume of downloaded files, snapshots and screenshots poses a significant challenge for efficient file management. This paper presents an automated file classification and organization system that leverages machine learning techniques to automate the process of file classification. The system dynamically monitors things such as download folders, detecting new file additions and applies a machine learning model to classify these files into predetermined categories based on their content and metadata. For instance, downloaded documents, images and executable files are automatically sorted into respective folders like Documents, Images and Software enhancing accessibility and management. So through automating the file classification, it not only reduces the administrative burden on users but also improves with the file retrieval. The method also has broader usage in the fields of data automation and management which can be scaled for large volume of data in a personal as well as enterprise settings.

Intelligent file management file classification downloaded files machine learning artificial intelligence.