1 Quick Start

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The machine learning hub (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). It runs native on Ubuntu, but will also run on GNU/Linux in general, and on MacOS and Windows with a few extra commands.

We can get started with using MLHub quickly without having to investigate the book which aims to further explain the how, the why, and the where. Details of the command line are presented in Chapter 2.

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 as explained in Section 2.1, 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 on installation and takes a few more commands to install dependencies.

Install MLHub by copying and pasting the following command line to a terminal running on your 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


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