mlhub 1.3.7

Machine learning model repository manager

UNDER DEVELOPMENT

Introduction

The machine learning hub is an open source project aimed at easily sharing pre-built machine learning models. The models are accessed and managed using the ml command from the mlhub package designed to install the model and run a demonstration within 5 minutes.

Visit the repository index on mlhub.ai where the models themselves can be browsed from the main pool.

Quick Start

The command line interface can be installed using PyPi:

$ pip3 install mlhub

Once installed you will be able to run the sample rain-tomorrow model assuming that you have the free and open source R statistical software package installed. The TL;DR version is below. Note that you type the command ml ... and that everything from the # to the end of the line is ignored (it’s a comment):

$ ml install   rain-tomorrow # Install the model named rain-tomorrow.
$ ml demo      rain-tomorrow # Run the demonstration of the model
$ ml display   rain-tomorrow # Graphical display of pre-built model.

The following commands are available and below is a brief description of each command:

$ ml                         # Show a usage message.
$ ml available               # List of pre-buld models on the MLHub.
$ ml installed               # List of pre-built models installed locally
$ ml install   rain-tomorrow # Install the model named rain-tomorrow.
$ ml readme    rain-tomorrow # View background information about the model.
$ ml commands  rain-tomorrow # List of commands supported by the model.
$ ml configure rain-tomorrow # Install required dependencies.
$ ml demo      rain-tomorrow # Run the demonstration of the model
$ ml print     rain-tomorrow # Textual summary of the model.
$ ml display   rain-tomorrow # Graphical display of pre-built model.
$ ml score     rain-tomorrow # Run model on your own data.

Different model packages will have different dependencies and these will be installed by the configure command.