Spotlight

Abstract

1. Introduction

Spotlight helps you to understand unstructured datasets fast. You can quickly create interactive visualizations and leverage data enrichments (e.g. embeddings, prediction, uncertainties) to identify critical clusters in your data.

Get started by installing Spotlight and loading your first dataset.

Interactively explore unstructured datasets from your dataframe.

2. Objective

Interactively explore unstructured datasets from your dataframe.

This project demonstrates how TypeScript, Computer Vision, Machine Learning can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm / yarn / pnpm
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/Renumics/spotlight.git
cd spotlight

pip install renumics-spotlight

pip install renumics-spotlight[analyzers]

# CPU support
pip install --extra-index-url https://download.pytorch.org/whl/cpu renumics-spotlight[torch]
# Default installation
pip install renumics-spotlight[torch]
# Specific CUDA version support
pip install --extra-index-url https://download.pytorch.org/whl/cu128 renumics-spotlight[torch]

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by Renumics and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.