How to Create a Linux Virtual Machine For Machine Learning Development With Python 3

Last Updated on August 21, 2019

Linux is an excellent environment for machine learning development with Python.

The tools can be installed quickly and easily and you can develop and run large models directly.

In this tutorial, you will discover how to create and setup a Linux virtual machine for machine learning with Python.

After completing this tutorial, you will know:

How to download and install VirtualBox for managing virtual machines.
How to download and setup Fedora Linux.
How to install a SciPy environment for machine learning in Python 3.

This tutorial is suitable if your base operating system is Windows, Mac OS X, and Linux.

Kick-start your project with my new book Machine Learning Mastery With Python, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

Benefits of a Linux Virtual Machine

There are a number of reasons that you may want to use a Linux virtual machine for Python machine learning development.

For example, below is a list of 5 top benefits for using a virtual machine:

To use tools not available on your system (if you’re on Windows).
To install and use machine learning tools without impacting your
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