How to Create a Perfect Machine Learning Development Environment With WSL2 on Windows 10/11

Everything included: terminal, Docker, Anaconda, Git, Jupyter Lab, GPU support, …

Bex T.

·

Follow

Published in

Towards Data Science

·

12 min read

·

Nov 29, 2022

448

5

Listen

Share

What is WSL, and why do you need it?

That’s it. I’ve had enough. The failed installations, error messages, memes making fun of Windows, people thinking they are cooler because they are using Linux…

That ends today by installing a fully-fledged Linux development environment right on top of the supposedly stupid Windows (10/11) using Windows Subsystem For Linux 2 (WSL2).

WSL2 enables you to run a complete Linux environment inside Windows. It has a dedicated file system and Linux terminal while allowing files and services to be seamlessly shared with Windows code editors and applications.

As a machine learning engineer or a data scientist, you will significantly benefit from a Linux environment. You'll find it much easier to install and work with technologies like TensorFlow, PyTorch, or Docker, as Linux utilizes system resources more smoothly, especially GPUs.

By the end of this tutorial, you will have a fully-fledged Linux environment, complete with the following:

• Customized terminal