{"repo":"AmirhosseinHonardoust/AI-Personal-Study-Tracker","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/AI-Personal-Study-Tracker","clone":"git clone https://github.com/AmirhosseinHonardoust/AI-Personal-Study-Tracker.git","description":"An AI-driven productivity tracking app built with Python, Streamlit, SQLite, and Machine Learning. It logs and analyzes study sessions, predicts productivity using Random Forest models, and visualizes key insights to help learners improve focus, habits, and overall academic efficiency.","language":"Python","stars":31,"topics":["ai","data-analytics","data-visualization","education","learning-analytics","machine-learning","productivity","python","random-forest","self-improvement"],"license":"MIT","category":"machine-learning","readme_excerpt":"AI-Powered Personal Study Tracker An intelligent productivity analytics app built with Python , SQLite , Machine Learning , and Streamlit . It empowers learners to track, visualize, and improve their study habits while using AI to estimate their expected productivity. --- Overview The AI-Powered Personal Study Tracker transforms daily study logs into actionable insights. It leverages a Random Forest Regressor to model productivity based on mood, distractions, study duration, caffeine intake, and more. You can: - Log study sessions (with mood, focus level, and caffeine) - Analyze study performance trends and patterns - Estimate expected productivity before studying - View aggregated insights and KPIs --- Project Structure --- Dashboard Preview Productivity Overview Session Log and Estimator --- Quickstart --- Tech Stack Layer Technology :-- :-- Frontend Streamlit + Plotly Backend SQLite ML Model RandomForestRegressor (scikit-learn) Data Handling pandas, SQLAlchemy Language Python 3.10+ --- Key Features - Log daily study sessions with mood, distractions, caffeine, and techniques - Predict productivity with ML model - Visualize time trends and subject-wise averages - Local SQLite database (portable and private) - Add new sessions interactively via the Streamlit sidebar - Estimate productivity in real-time --- Data Schema Column Description :-- :-- date Session date (YYYY-MM-DD) start time / end time HH:MM 24h format duration min Computed from start–end times subject Math, Physic","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/AI-Personal-Study-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."}