Predicting Mental health disorders using Machine Learning for employees in technical and non-technical companies

mental health has always been an important and challenging issue, especially in the case of working Professionals. The modernized (hectic) lifestyle and workload take a toll over people over time making them more prone to mental disorders like mood disorder and anxiety disorder. Thus, the risk mental health problems increase in working professionals. To deal with this problem industries provide mental health care incentives to their employees, but it is not enough to deal with the problem. In this paper, we utilize the data from mental health survey 2019 that contains the data of working professionals for both tech and non-tech company employees. We process data to find the features influencing the mental health of employees or features that can help to predict the mental health of the employee the feature can be either personal or professional. We apply multiple machine learning algorithms to find the model with the best accuracy. We take precision and recall as the measure to check the performance of different ML models.