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Syllabus
- Introduction
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Class Intro and Agenda 2 min
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What is AI, ML and DL? 2 min
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Why ML at the Edge? 2 min
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ML Edge Applications 2 min
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Why is ML Popular Now? 3 min
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ML Development Flow 6 min
- Data Science
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Selecting and Collecting Data 11 min
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Today's Problem 4 min
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Lab 1: Collection of Raw Light Data 10 min
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Organizing the Data 8 min
- MPLAB® ML Suite
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Overview 2 min
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Lab 2: Constructing the ML Project 11 min
- Problem Classification
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Selecting and Building the Model 12 min
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Lab 3: Model Creation 14 min
- Running Models on an Edge Computer
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Deploying the Model 5 min
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Lab 4: Exporting your Model 6 min
- Optimizing Models for Resource Constrained Parts
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Example Application 3 min
- Wrap up
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Summary 1 min
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Lab Files for Download
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Shining a Light on Artificial Intelligence and Machine Learning
This class will take a journey through artificial intelligence and machine learning and how you can use it in a simple embedded application (Dec 2024)
Are you intrigued or concerned by the possibilities of artificial intelligence? Whilst we are not going to attempt to build the next Terminator, this class will take a journey through artificial intelligence and machine learning and how you can use it in a simple classification application. We will begin by looking at the perceived benefits of AIML and apply it to a simple case study where we teach the microcontroller to detect what sort of light is shining on a sensor. We will cover techniques for capturing and processing the sampled signals on a typical microcontroller and the factors that you should consider in your design. Having captured the data, we will use the Microchip MPLAB® Machine Learning Development Suite to process it and build an ML model able to discriminate between the various modes of our light source. We will then test our model on hardware and evaluate its performance under real conditions. After completion of this course, attendees will be able to add artificial intelligence to their own designs.