Diamond Price Predictor

Overview

The Diamond Price Predictor is a simple web application that allows users to upload diamond-related data, visualize the data, and predict the price of a diamond based on various features. It's a handy tool for exploring and analyzing diamond data.

Features

• Upload CSV data files.
• Visualize data with scatter plots, bar plots, and line plots.
• Train a machine learning model on the data.
• Predict diamond prices based on user inputs (carat, depth, table, dimensions).

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/daniel1kp/diamond-price-predictor.git
   

2. Change to the project directory:

   cd diamond-price-predictor
   

3. Install the required Python libraries:

   pip install -r requirements.txt
   

Usage

1. Run the web app using Streamlit:

   streamlit run main.py
   

2. Open the app in your web browser by following the link provided.

3. Upload your diamond data in CSV or JSON format.

4. Choose a case (Case 1, Case 2, or Case 3) to preview and analyze data.

5. Visualize data using the available options in the dropdown.

6. Use the sidebar to input diamond parameters and predict the price.

Data Sources

The dataset used in this project can be found on Kaggle. You can access the dataset here.

Deployment

The web application can be accessed here.