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TL;DR MLHub is both a command line tool and a repository of pre-built models for artificial intelligence (AI), machine learning (ML), and data science (DS).

Let’s get started without having to wade through the book first to find out the how, the why, and the where.

The MLHub command line tool supports any number of commands that are exposed through individual model packages installed from the repository. Some basic commands are provided by the MLHub command line itself.

To get started, the simplest approach is to use Ubuntu 22.04, perhaps in a virtual machine on your own desktop computer or else in the cloud. That could take a little time to set up, possibly up to 30 minutes. MLHub can run on Windows and MacOS but it is not so smooth to do so.

Once you have access to Ubuntu, install MLHub by copying and pasting the following command line to a terminal running on the Ubuntu desktop:

pip install mlhub

Then configure the MLHub ecosystem:

ml configure

Now find a MLHub package to explore:

ml available

We will use the k-means package as described in Chapter 7. The following sequence of commands illustrate the typical setup workflow for any MLHub package:

ml install   kmeans

ml configure kmeans

ml readme    kmeans

ml commands  kmeans

ml demo      kmeans

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Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0