seeq-azureml 0.1.0

Seeq Add-on that integrates with Microsoft Azure Machine Learning (AML) models as a web service

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Introduction

seeq-azureml provides an example framework that allows a data scientist working in Azure ML Studio and a plant engineer or subject matter expert (SME) working in Seeq to collaborate and develop an effective, sustainable solution for high value problems in manufacturing.

This python module integrates with Microsoft Azure Machine Learning (AML) models as a web service and can be installed as a Seeq Add-on in Seeq Workbench. The plant engineer and/or SME interacts with the module through an easy to use UI from which they can accomplish critical activities such as ad hoc/historical evaluations, model deployment in real time, scaling to other assets, etc.

The Seeq Add-on is distributed as an example of a collaborative workflow between data scientists (model builders) and plant engineers/SMEs (model consumers). Users are encouraged to fork the repo and make the necessary modifications/enhancements that addresses the specific needs/workflows of their organization.

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Documentation

The documentation for seeq-azureml can be found here.

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User Guide

seeq-azureml User Guide provides a more in-depth explanation of how this Seeq Add-on enables engineers and SMEs in OT to directly interface with models built by data science teams in Azure ML Studio and that have been registered and deployed in an AML endpoint as a cloud service.

For additional details on the Data Scientist workflow, take a look at this video.

For additional details on the Engineering workflow, take a look at this video.

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Installation

The backend of seeq-azureml requires Python >3.7 or later.

Dependencies

See requirements.txt file for a list of dependencies and versions. Additionally, you will need to install the seeq module with the appropriate version that matches your Seeq server. For more information on the seeq module see seeq at pypi

User Installation Requirements (Seeq Data Lab)

If you want to install seeq-azureml as a Seeq Add-on Tool, you will need:

• Seeq Data Lab (> R50.5.0, >R51.1.0, or >R52.1.0)
• seeq module whose version matches the Seeq server version, and the version of SPy >= 182.25
• Seeq server admin access
• Enable Add-on Tools in the Seeq server

User Installation (Seeq Data Lab)

The latest build of the project can be found here as a wheel file. The file is published as a courtesy and does not imply any guarantee or obligation for support from the publisher.

1. Create a new Seeq Data Lab project and open the Terminal window
2. Run pip install seeq-azureml
3. Run python -m seeq.addons.azureml [--users <users_list> --groups <groups_list>]
4. Create an aml_config.ini file in the ~/.seeq folder of the Seeq Data Lab Project with the information required to connect to the Azure ML services. The file must contain the options specified in here

Note: If Step 3 gives an error make sure that the seeq module is >= a.b.c.182.25 where a.b.c are explained here

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Development

We welcome new contributors of all experience levels.

Important links

• Official source code repo: https://github.com/seeq12/seeq-azureml
• Issue tracker: https://github.com/seeq12/seeq-azureml/issues

Source code

You can get started by cloning the repository with the command:

git clone [e-mail]:seeq12/seeq-azureml.git

Installation from source

For development work, it is highly recommended creating a python virtual environment and install the package in that working environment. If you are not familiar with python virtual environments, you can take a look here

Once your virtual environment is activated, you can install seeq-azureml from source with:

python setup.py install

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Changelog

The changelog can be found here

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Support

Code related issues (e.g. bugs, feature requests) can be created in the issue tracker

Maintainer: Seeq

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Citation

Please cite this work as:

seeq-azureml
Seeq Corporation, 2021
https://github.com/seeq12/seeq-azureml