Local-first Android strength training: fast workout logging, recovery, plans, progress, and an honest Iron Ledger.

End-to-end fitness analytics project using Python, SQL, and Power BI to track workout adherence, muscle group performance, and strength progression through an interactive dashboard.

🔥 Advanced machine learning platform for accurate calorie burn prediction using comprehensive Kaggle fitness datasets. Features real-time predictions, professional analytics, and fitness industry integration capabilities.

Fitness analytics project using Python, SQL, and Power BI

End-to-end health and behavioral analytics project using SQL, BigQuery, and Tableau.

A machine learning web application built with Streamlit and XGBoost to accurately predict the calories burnt during a workout based on physical and physiological parameters.

End-to-end fitness analytics dashboard using Python, SQL, Streamlit, and machine learning.

Interpreting wearable fitness data through a physiology lens: HRV, VO2 max estimation, sleep tracking accuracy, training load metrics, and device validation studies.

Power BI dashboard for gym operations: membership analysis, financial performance, and fitness KPIs.

Privacy-first, local-first wearable analytics combining Garmin data with transparent recovery, sleep, training-load, and coaching insights. Explainable by design, useful without a cloud.

Model Context Protocol (MCP) server for Intervals.icu athletic data & fitness analytics with fastembed tool routing and ContextForge Gateway support.

🏋️ Analyze workout data to enhance training consistency, muscle performance, and strength progression with a comprehensive fitness analytics dashboard.