{"repo":"AmirhosseinHonardoust/AI-Productivity-Tracker","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/AI-Productivity-Tracker","clone":"git clone https://github.com/AmirhosseinHonardoust/AI-Productivity-Tracker.git","description":"Analyze and predict daily productivity using SQL, machine learning, and psychology. This project combines behavioral data, circadian rhythm analysis, and ElasticNet regression to model focus, stress, and performance, transforming work patterns into actionable insights.","language":"Python","stars":35,"topics":["behavioral-analytics","data-science","data-visualization","elasticnet","feature-engineering","human-performance","machine-learning","mental-health","portfolio-project","predictive-modeling"],"license":"MIT","category":"machine-learning","readme_excerpt":"AI Productivity Tracker (SQL + ML + Psychology) Predict and analyze daily productivity using behavioral data, SQL feature engineering, and machine learning , integrating psychological principles such as circadian rhythm , stress-performance dynamics , and habit efficiency . This project demonstrates how modern data science can quantify human productivity in knowledge work, blending psychology, data engineering, and predictive analytics . --- Overview This project models daily productivity based on personal and contextual factors such as sleep, stress, meetings, breaks, and focus patterns. It uses: - SQL (SQLite) for feature engineering and psychological metric derivation - Python (pandas, scikit-learn) for data processing, training, and visualization - ElasticNet Regression for interpretable prediction - Behavioral Science Insights to ensure meaningful features --- Project Structure --- Data Description Column Description -------- -------------- sleep hours Hours of sleep the previous night chronotype Morning or evening preference focus start hour Hour when deep work begins deep work minutes Minutes of uninterrupted work meetings minutes Total meeting duration late meetings minutes Evening meetings (negative for energy) breaks count Number of breaks during the day avg break minutes Average break duration context switches Task changes / app switches notifications Distractions from notifications steps , hydration glasses , caffeine mg Physical activity and health proxies stress","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/AI-Productivity-Tracker/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}