What if you could go beyond building machine learning models and create a web application to showcase your results to the world? Introducing Mercury, the simple free tool to turn your Jupyter Notebooks into interactive web apps. Ready to present your work to the world in a more interactive way?

A Look at the Project Ahead

This hands-on project isn't just about predicting diamond prices with machine learning. It's also about tapping into Mercury to transform your predictions into immersive web experiences.

By the end of this project, you will be able to:

Master the data preprocessing pipeline, including feature selection, encoding, and handling outliers.
Explore and understand the concepts of correlation analysis and feature visualization.
Build and evaluate various machine learning models, interpreting metrics like MAE, MSE, and R-squared.
Identify and choose the most effective model for making future diamond price predictions.
Use open-source framework, Mercury, to share the exciting outcomes from the Jupyter Notebook with a global audience through the web.

What You'll Need

This guided project requires basic knowledge of Python and database queries. However, don't worry if you don't have much experience with the above. This project will explain each step along the way, and you may learn as-you-need along the way.

IBM Skills Network Labs environment also comes with many technical requisites pre-installed to save the hassle of setting everything up, so we won't be dealing with any environment issues.

Build an AI Web App for Diamond Price Prediction

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