The problem MindMate solves

In a world where stress and mental health concerns are prevalent, MindMate steps in as a solution to predict an individual's mental health status. With the rise in mental health issues, it's often challenging to recognize when one is experiencing stress or anxiety. Mind Mate provides a convenient tool to assess mental well-being through machine learning algorithms. By offering insights into mental health, it empowers individuals to seek appropriate support and interventions, ultimately promoting better overall well-being

Challenges we ran into

Getting around the complex world of mental health data gathering was a big challenge because it took a lot of work to find reliable and complete datasets. Strict attention to detail and exacting validation procedures were necessary to guarantee the data's quality, relevance, and suitability for predictive analysis. Complexity was also increased by the processing of various data formats, fixing errors, and encoding categorical variables for model training. Furthermore, it took a great deal of trial and error and fine-tuning to get the best possible model accuracy among the complexity of mental health prediction. In order to provide a reliable and approachable solution, there were difficulties in designing the application, guaranteeing smooth user interaction, and resolving any deployment concerns when implementing the machine learning model using Streamlit.