CFI

N/A

Multi-Modality Mental Health Analysis Model

The project aims to assist mentAImage's data and AI/ML engineers in enhancing their multi-modality models for analyzing mental health and wellness. The focus is on training and fine-tuning models to assess text sentiment, voice tone, and creative expression to predict burnout in organizational settings. Learners will apply their classroom knowledge of machine learning and data analysis to improve model accuracy and efficiency. The project involves understanding the nuances of mental health indicators and integrating them into a cohesive analytical framework. By doing so, learners will contribute to a model that can provide valuable insights into employee well-being and organizational health. - Analyze existing datasets related to text, voice, and creative expressions. - Develop and fine-tune machine learning models to improve prediction accuracy. - Collaborate with team members to integrate different data modalities into a unified model. - Test and validate the model's performance in predicting burnout.

Analyse du contrôle interne

Gestion et contrôle interne.