This Flask-based application recommends similar products based on user preferences such as price, favorites, and reviews. Ideal for users searching for personalized baby product recommendations on Etsy.
- Custom Preferences: Filter products by price range, popularity, and number of reviews.
- Data Analysis: Uses cleaned dataset for accurate recommendations.
- Machine Learning Models: Random Forest, Gradient Boosting, and SVC models applied for precise predictions.
Flask/
│
├── app.py # Main Flask application
├── Cleaned_data.csv # Dataset used for recommendations
├── templates/
│ ├── index.html # Homepage with preference input
│ ├── recommendations.html # Displays recommendations
└── static/
├── background.jpg # Background image- Clone the repository:
git clone <repository-link>
- Navigate to the project directory:
cd flask - Install the required packages:
pip install -r requirements.txt
- Run the application:
python app.py
- Visit
http://127.0.0.1:5000/in your browser. - Enter preferences such as price, number of favorites, and reviews.
- View the list of recommended products.
-
Price Distribution:
-
Correlation Heatmap:
- Random Forest achieved 100% accuracy.
- Gradient Boosting and SVC yielded great results with accuracy and feature importance.
