Problem Statement
People starting their fitness journey often don't know which exercises suit their body type and goals. A generic workout plan rarely fits everyone. This project predicts a personalized workout recommendation based on basic user attributes.
Model & Workflow
Model: Random Forest Classifier
Dataset Prep→
Preprocessing→
Label Encoding→
BMI Calculation→
Model Training→
Joblib Save→
Flask Integration
Dataset Features
- Age
- Weight
- Height
- BMI
- Goal
- Fitness level
- Exercise
Supported Goals
Fat Loss
Muscle Gain
Upper Body
Lower Body
Full Body
Core
App Features
- Personalized workout recommendations
- Workout images
- Built-in 60-second workout timers
- Pause and resume
- One active timer at a time
- Completion states
- Sound effects
- Responsive interface
Technologies Used
PythonScikit-learnPandasNumPy
JoblibFlaskHTMLCSS
JavaScriptRender
No specific model accuracy is reported — the focus is on a working recommendation application.