Synaptica

Synaptica is a predictive system designed to analyze how social media usage impacts students daily lives, leveraging machine learning models trained on a dataset of over 3 million records. The system combines multiple analytical approaches, including linear regression, logistic regression, and decision trees, to identify patterns and correlations between social media usage and key variables such as academic performance, mental health, and social relationships. On the backend, a Flask-based API was developed to handle data processing, execute predictive models, and return interpretable results to the user. The system is designed to provide clear and actionable insights, allowing users to evaluate their behavior and compare it against large-scale real-world data. Beyond prediction, the platform serves as a decision-support tool, helping users understand how their digital habits may influence different aspects of their lives. The project combines data analysis, statistical modeling, and backend development to solve a real-world problem, with a strong focus on interpretability, scalability, and efficient processing of large datasets.