Analyze your data from Garmin, Suunto, Coros to one centralized app
Local-first Python CLI that turns Garmin Account Data Export into reproducible running, FIT, sleep, HRV, and training datasets with QA and provenance.
Open-source, local-first training platform: calendar, AI assistant, Garmin & WHOOP sync — plus a TypeScript SDK, CLI, and MCP server for FIT, TCX, ZWO, and Garmin Connect workout files.
The_Fit_District is a comprehensive gym membership dataset comprising seven interconnected tables—Branches, Members, Subscriptions, Trainers, Plans, Attendance, and Payments—designed to model real-world fitness center operations, track member activity, manage trainer assignments, analyze plan utilization, and monitor attendance patterns.
TypeScript SDK for the TrainingPeaks platform
EDA and visualization of FitBit fitness tracker data to identify user behavior trends and deliver product recommendations for BellaBeat. Google Data Analytics Certificate capstone.
Transforming Garmin wearable telemetry into behavioural intelligence using Python, analytics, predictive modelling and Power BI.
Cross-platform Agent Skill and Python CLI for decoding, deduplicating, and reconciling Garmin FIT workout files
Pull per-length swim data out of Polar Flow — the lap times Polar computes, shows in its web app, and omits from every file export — into a local SQLite database.
Local-first, read-only Google Health archive CLI — sync, query, and export your Google Health data to a local SQLite archive.
Professional Python tool to clean up the Garmin Data Export mess. Auto-discovers activity files across multi-part ZIPs, renames them using intelligent metadata extraction with offline GPS-timezone detection, and provides Lightroom-ready GPX files for ultimate data sovereignty.
Machine learning project for predicting calories burned during gym workout sessions using Python, EDA, regression models, hyperparameter tuning, and SHAP explainability.
Free local-first Polar Flow to Garmin Connect migration tool. Convert Polar Flow ZIP/JSON exports to TCX/FIT in your browser.
Project: Core Feature Implementation and Initial User Testing. Created at https://spectra.codes, which is owned by @Drix10
Use Strava's official MCP from Codex and OpenCode without creating a developer app. Local macOS Keychain and privacy-first streams.
End-to-end fitness data analysis in Alteryx — data cleaning, BMI & lifestyle analysis, sleep/step patterns, and weekly activity insights. DataCamp Certified.
Examples of how to generate reports using Python for a Cordelia database
Bellabeat case study analyzing consumer fitness behavior using public Fitbit data (Python).
An R-based analytics project for exploring and modeling gym activity data from 973 users. The pipeline performs descriptive analysis and statistical inference, while an interactive R Shiny app supports automated modeling, visualization, and result export for exploratory analysis.
MCP server for Strava API - Connect AI agents to your athletic data. Retrieve athlete stats, activities, lap splits, and GPS/heart rate streams. Built with Python and FastMCP.
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