In the current era where mental health awareness is increasingly crucial, the Depression Detector aims to identify signs of depression effectively using digital data. This project leverages data from sources like social media posts, forum discussions, and text messages to detect depressive behaviors early and accurately. The system uses advanced machine learning models to analyze text for indicators of depression, offering a faster, less invasive alternative to traditional diagnostic methods. This proactive approach helps in identifying individuals who might not seek help due to stigma or lack of awareness, providing them with timely support and resources to improve health outcomes.