• Pratiksha Maruti Nikam
• Prof.Shital Jade
• Samruddhi Sujit Patil
• Swejal Maruti Kobal

: Stress, depression, and other mental health issues are becoming increasingly prevalent worldwide, affecting people of all ages. To address this problem, we have developed an application that utilizes machine learning techniques to detect and analyze the root causes of mental health issues such as stress, anxiety, and depression. Our project utilizes various machine learning algorithms that offer greater accuracy and are more effective than traditional techniques. We gathered data from social media networks and utilized different methods to detect early signs of major depressive disorders (MDDs) using machine learning. We performed an analysis of the datasets to understand the behavioral patterns of individuals suffering from mental health issues. We used facial expressions, gestures, speech, and text analysis to identify the root causes of the mental health issues. In addition, we used different gestures of the eyes, mouth, nose, and hands to detect moods such as anger, happiness, sadness, and neutral emotions through an emotion detection system using image and video processing. Our application aims to detect and analyze mental health issues at an early stage, allowing individuals to seek the necessary help and support. The use of machine learning techniques allows for greater accuracy and effectiveness in identifying the root causes of mental health issues, enabling individuals to take the necessary steps to improve their mental well-being.

Supervised machine learning, medical science, Naïve biased, CNN, Image processing

"PYTHON BASED DEPRESSION DETECTION SYSTEM USING MACHINE LEARNING & ALGORITHM’S", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.d595-d599, May-2023, Available :http://www.jetir.org/papers/JETIR2305380.pdf

"PYTHON BASED DEPRESSION DETECTION SYSTEM USING MACHINE LEARNING & ALGORITHM’S", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppd595-d599, May-2023, Available at : http://www.jetir.org/papers/JETIR2305380.pdf