Personal Fitness Tracker Web App 🚀🏋️♂️ Overview This AI-powered Personal Fitness Tracker is a Streamlit-based web application that predicts the number of calories burned during exercise using Machine Learning. By entering details like Age, BMI, Duration, Heart Rate, Body Temperature, and Gender, users receive an instant calorie burn estimate. The app provides personalized insights and compares user data with others in the dataset, making it a great tool for fitness tracking.
🔹 Key Features ✅ User-Friendly Interface – Simple sliders and buttons for easy data input. ✅ ML-Powered Predictions – Uses a Random Forest Regressor to estimate calorie burn. ✅ Insightful Analytics – Compare your stats with others to understand where you stand. ✅ Similar Case Analysis – Find users with similar fitness profiles for better context. ✅ Data Visualization – Interactive charts for trends and performance analysis.
🔹 Tech Stack & Methodology 🔹 Python, Streamlit for web app development. 🔹 Pandas, NumPy, Matplotlib, Seaborn for data handling & visualization. 🔹 Scikit-learn (RandomForestRegressor) for machine learning predictions. 🔹 CSV Data Processing & Feature Engineering to improve model accuracy.
The model is trained on real-world exercise and calorie data, ensuring reliable results. BMI is calculated dynamically, and gender is one-hot encoded to maintain accuracy. The app also highlights how your exercise stats compare with other users, providing valuable insights into your fitness levels.