Machine Learning Foundations: Prototyping on the Edge

Machine Learning Foundations: Prototyping on the Edge

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 21m | 241 MB

As AI and compute power continue to grow, so does the need and opportunity for decentralized intelligence or intelligence “on the edge.” Prototyping allows product designers, product managers, and developers to focus on exploring product ideas, without a deep knowledge of theory, and tools and hardware now available make this possible. In this course, technologist, designer, and speaker Robert Gallup guides you through the process of prototyping machine learning on the edge. Robert begins with an overview of machine learning, including machine learning elements, workflow, and ethics. Next, he then discusses prototyping, and presents a scenario and plan for the voice recognition prototype developed in the course. Robert then walks you through how to prepare software and hardware, as well as how to define, train, and deploy a machine learning model. Finally, he shows you how to extend your prototype and discusses considerations in making the move from prototype to production.

Table of Contents

Introduction
1 Welcome
2 Course resources

Machine Learning Overview
3 Introduction to machine learning on the edge
4 Machine learning elements
5 Machine learning workflow
6 Machine learning ethics

Prototyping
7 Prototyping overview
8 The prototype plan

Preparing Software and Hardware
9 Set up the Arduino IDE
10 Arduino hardware
11 Run a machine leaning demo

Defining and Training an ML Model
12 Create a project in Edge Impulse
13 Acquiring data
14 Define the machine learning pipeline
15 Training the model

Deploying the ML Model
16 Deploying to computer
17 Deploying to Arduino
18 Running the model

Extending Your Prototype
19 Adding LED functionality
20 Adding keyboard functionality
21 Challenge Add another keyword
22 Solution Add another keyword

Conclusion
23 From prototype to production
24 Final thoughts

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