Jewelry Ring Appraisal

Overview

Jewelry Ring Appraisal is a machine learning model and web application designed to evaluate the value of jewelry rings. The project combines a Flask web app with a Random Forest regression model to provide accurate appraisals based on various jewelry features.

Features

• Machine Learning Model: Utilizes a Random Forest regressor for predicting jewelry ring values.
• Flask Web Application: Provides an interactive interface for users to input jewelry data and receive appraisals.
• Data Visualization: Displays appraisal results and visualizations in a user-friendly format.

Datasets

The app uses the following datasets for training and evaluation:

• Cartier Jewelry Catalog: cartier_catalog.csv
• Jewelry Data: jewelry.csv

Technologies Used

• Machine Learning: Python, Scikit-Learn, Random Forest
• Web Development: Flask, HTML, CSS, Bootstrap, JavaScript, jQuery
• Data Science: Pandas, Jupyter Notebook
• Data Cleaning: Data preprocessing and feature engineering