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Mental Health problem prediction of Tech Employees Using Machine Learning
Abstract
In this era rapid societal changes, in addition to technology improvements, might pose problems and stress for the future generations. Individuals and society as a whole must place a high priority on mental health and well-being in order to reduce the detrimental effects of these developments. Individuals should give more importance to their own particular ideals and ambitions than just keeping up with society's pace. This kernel's goal is to identify the factors that affect someone's mental health based on this dataset. In 2014, attitudes towards mental health as well as the prevalence of mental health issues in the tech industry were assessed. This kernel seeks to create a methodical approach to comprehending mental
Health in the workplace, in contrast to the other kernels. Is there a preliminary action that must be taken? There are typically many creative kernels on many issues, but only a small number are dedicated to addressing the issues of how to start on issues in medicine, particularly those relating to local knowledge. This section outlines prostate cancer and how to identify it. Additionally, we have completed Electronic Design Automation, created a dataset, and established a dataset.
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P. Kumar, R. Chauhan, T. Stephan, A. Shankar and S. Thakur, "A Machine Learning Implementation for Mental Health Care. Application: Smart Watch for Depression Detection," 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2021, pp. 568-574, doi: 10.1109/Confluence51648.2021.937719
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