ML-Sandbox

Python Flask Machine Learning Data Science Jupyter
⏱ 1 min read
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Overview

ML-Sandbox allows users to run machine learning experiments directly from the browser. Unique in its architecture, it connects a web frontend to a Jupyter Notebook backend to execute Python code dynamically.

Key Features

  • 📂 Drag & Drop Upload: CSV dataset support
  • 🧠 Interactive Algorithms: Classification, Find-S, Candidate Key
  • ⚡ Jupyter Integration: Executes logic via notebooks
  • 📊 Auto-Visualization: Renders results instantly on the web UI

Tech Stack

TechnologyPurpose
JupyterML Execution Environment
FlaskBackend Server
PythonLogic Core
Pandas/ScikitData libraries

Getting Started

git clone https://github.com/Hritikraj8804/ML-Sandbox.git
cd ML-Sandbox/backend
pip install -r requirements.txt
python app.py