Feature: Embedded design


Figure 3: The ML workflow has many stages outside the traditional embedded IDE


Te Jupyter ecosystem also provides an IDE called Jupyter


Labs. Tis allows work with multiple notebooks simultaneously, and integrates other tools such as editors, terminals and a visual debugger. However, as we will see later, many of these features are


duplicated by VS Code which may be more convenient for an embedded developer.


Google Colaboratory One popular option for running Jupyter notebooks is Google Colaboratory, commonly known as Google Colab, which provides: • Free cloud-based computing resources • GPU acceleration for training models • Browser-based Jupyter notebook execution.


Figure 4: The SDS framework is used to record raw and post algorithm data for future training


Figure 5: The SDS framework can replay recorded data to the algorithm under test in either hardware or simulated environments


18 May 2026 www.electronicsworld.co.uk


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