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Configuring an Open-Source Linux Distribution for Machine Learning

Description

I set up a secure and efficient machine learning environment on an open-source Linux distribution (Ubuntu 24.04) by installing Python, Jupyter Notebook, and essential libraries like TensorFlow, PyTorch, and NumPy. The setup also focused on security, including the creation of a dedicated user for ML tasks, configuring a firewall with UFW, and enhancing protection with Fail2Ban and unattended upgrades. This project provides a solid foundation for ML development with both functionality and security in mind.

Utilities Used

  • Python 3
  • Pip
  • Jupyter Notebook
  • TensorFlow, PyTorch, NumPy, Pandas
  • UFW (Uncomplicated Firewall)
  • Fail2Ban
  • Unattended-Upgrades
  • OpenSSH
  • User Management Tools

Project Walk-through

System Update and Python Setup


Installed Jupyter Notebook


Installed ML Libraries


Created a Dedicated ML User



Configured UFW Firewall


System Hardening


Tested the Environment

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Topics

linux machine-learning os-configuration ml-environment-security

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