Real-time Machine Learning (ML) pipelines
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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.
Video
If you'd like to watch a video before stepping through this tutorial, you can view the following video on the Quix YouTube channel:
Prerequisites
To complete this tutorial you need the following:
- A Quix Cloud account.
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- Python3 installed.
- Jupyter Notebook to train your model and load data for training. See How to work with Jupyter Notebook for further information.
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:
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Create your data - You learn how to create some data to work with in the rest of the tutorial.
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Import data - You learn how Quix makes it easy to import your data into Jupyter Notebook, by providing you with ready-to-use code.
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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.
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Deploy your ML model - You learn how to deploy your ML model to Quix.
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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.