The Personal Fitness Tracker! This Streamlit-based web application allows users to predict the calories burned during exercise. The app leverages machine learning models to provide accurate predictions and helps users track their fitness journey over time.
🔥 Super excited to share my very first launch on Product Hunt – Personal Fitness Tracker!
This is a Streamlit-based web app that helps you predict calories burned during exercise with the power of machine learning. Just enter a few details like Age, Gender, BMI, Duration, Heart Rate, and Body Temperature, and the app gives you real-time calorie predictions.
✨ What makes it special
Automatically picks the best ML model (Logistic Regression, SVM, or Random Forest)
Tracks and saves your past predictions
Visualizes your fitness journey with charts
Lets you export your history as CSV for easy tracking
💡 I built this project to combine fitness + AI, making workout tracking a little smarter and more data-driven.
I’d love to hear your feedback, suggestions, and feature ideas to take this to the next level. 🙌
Congrats on your first launch! 🎉 Track Fit looks like such a smart way to combine fitness with AI. I was actually looking for something like this. Excited to give it a try! 💪
This is really cool, I've wanted something this to help with my marathon training. Do you plan on integrating with the apple watch or any wearables?
Hi @kimmi_kumari Pretty cool to see. I'm a professional golfer (when I'm not helping build AI-powered interactive learning), so anything in the health and wellness space is always on my radar. I really LOVE this idea, because it will help me plan my workouts + food intake to make sure I'm in a deficit when I'm touring / on the road. I have two questions: Are you planning to integrate with actual trackers to measure accuracy, and how do you hope to account for changes in women's body in a month? You're on to something awesome, though! Excited to see where this goes.
Congrats on the launch. What kind of users do you see trying this first people already into quantified self and tracking everything or more casual fitness folks looking for a simple way to measure progress
About TrackFit on Product Hunt
“Progress your fitness goals using machine learning”
TrackFit launched on Product Hunt on September 16th, 2025 and earned 103 upvotes and 9 comments, placing #20 on the daily leaderboard. The Personal Fitness Tracker! This Streamlit-based web application allows users to predict the calories burned during exercise. The app leverages machine learning models to provide accurate predictions and helps users track their fitness journey over time.
TrackFit was featured in Health & Fitness (82.5k followers), Artificial Intelligence (466.3k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 131.2k products, making this a competitive space to launch in.
Who hunted TrackFit?
TrackFit was hunted by Kimmi Kumari. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how TrackFit stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Kimmi Kumari