DEPRESSION-DETECTION-USING-MACHINE-LEARNING and Depression-Detection-System-Using-Machine-Learning

About DEPRESSION-DETECTION-USING-MACHINE-LEARNING

Nihalahamad1905/DEPRESSION-DETECTION-USING-MACHINE-LEARNING

Depression detection using machine learning is a vital area of research given the global burden of mental health disorders. This project explores two primary methodologies: leveraging depression quiz tests and analyzing sentences.

About Depression-Detection-System-Using-Machine-Learning

SUBHADIPMAITI-DEV/Depression-Detection-System-Using-Machine-Learning

This project develops a Depression Detection System using Machine Learning on Twitter data. It predicts depression by analyzing tweets with SVM, Logistic Regression, Decision Trees, and NLTK in Python.

This system helps identify potential signs of depression by analyzing text from social media posts, specifically tweets. It takes raw Twitter data as input and uses machine learning to output predictions about the emotional state expressed in the tweets. This tool would be useful for mental health researchers, public health organizations, or social scientists interested in large-scale sentiment analysis related to mental well-being.