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

1. Clone the repository:

   git clone <repository-link>

2. Navigate to the project directory:

   cd flask

3. Install the required packages:

   pip install -r requirements.txt

4. 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.