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Real-time Machine Learning (ML) pipelines


This tutorial is out of date. Please check the tutorials overview for our latest tutorials.

In this tutorial, you learn how to extract data from Quix to train your Machine Learning (ML) model in Jupyter Notebook. You then learn how to deploy this model to Quix, so ML can be used to process your data in real time.


If you'd like to watch a video before stepping through this tutorial, you can view the following video on the Quix YouTube channel:


To complete this tutorial you need the following:

There are some other libraries that need to be installed, but instructions on how to do this are given when required.

The parts of the tutorial

This tutorial is divided up into several parts, to make the learning experience more manageable. The parts are summarized here:

  1. Create your data - You learn how to create some data to work with in the rest of the tutorial.

  2. Import data - You learn how Quix makes it easy to import your data into Jupyter Notebook, by providing you with ready-to-use code.

  3. Train your ML model - You learn how to train an ML model. For this tutorial, this is done in Jupyter, but could also be done in Quix.

  4. Deploy your ML model - You learn how to deploy your ML model to Quix.

  5. Summary - In this concluding part you are presented with a summary of the work you have completed, and also some next steps for more advanced learning about Quix.

Get some data