Course 3: Deploying TinyML

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Chapter 4 · Course 3

Deploying TinyML

End-to-end deployment with TensorFlow Lite for Microcontrollers. Covers embedded hardware/software, TFLite Micro internals, and hands-on labs deploying keyword spotting, visual wake words, and gesture recognition on Arduino.

Textbook companion: Vol I Ch 11, 13 · Arduino & Seeed Kits

§4.1 Welcome to Deploying TinyML

Topic Type
Welcome to TinyML3 Reading
Welcome Message from VJ Slides
Course 1 and 2 Recap Reading
TinyML Application Deployment Preview Slides
The TinyML Kit Reading
TinyML Course Kit Overview Slides
How the Course is Structured Slides

§4.2 Getting Started

Topic Type
C++ for Python Users Reading
Setting up your Hardware Reading
Setting up your Software Reading
The Arduino Blink Example Reading
Testing the TensorFlow Install Reading
Testing the Sensors Reading

§4.3 Embedded Hardware and Software

Topic Type
Embedded System Slides
Diversity of Embedded Systems Reading
Embedded Computing Hardware Slides
Diversity of Embedded Microcontrollers Reading
Embedded I/O Slides
Transducer Modules and Wireless Communication Reading
Embedded System Software Slides
Arduino cores, frameworks, mbedOS, and 'bare metal' Reading
Embedded ML Software Slides

§4.4 TensorFlow Lite Micro

Topic Type
What is TensorFlow Lite for Microcontrollers? Reading
TFMicro: The Big Picture Slides
TFLite Micro: Interpreter Slides
MCU Memory Hierarchy Reading
TFLite Micro: Model Format / FlatBuffer Slides
TensorFlow Lite Flatbuffer Manipulation Colab Colab
TFLite Micro: Memory Allocation (Tensor Arena) Slides
TFLite Micro: NN Operator Support (OpsResolver) Slides
TFLite Micro Developer Design Principles Reading

§4.5 Keyword Spotting

Topic Type
TinyML "Keyword Spotting" Workflow Reading
KWS Application Architecture Slides
KWS Initialization Slides
KWS Pre-processing Slides
KWS Inference Slides
KWS Post-processing Slides
KWS Summary Slides

§4.6 Custom Dataset Engineering for Keyword Spotting

Topic Type
Recap Dataset Engineering Reading
Introducing Custom Dataset for KWS Slides
Things to Consider for Your Data Collection Plan Reading
Building a Custom Dataset Reading
Train and Deploy Your Custom Dataset KWS Model Reading

§4.7 Visual Wake Words

Topic Type
Recap: What are Visual Wake Words? Reading
Person Detection Application Architecture Slides
Person Detection with KWS: MultiModal Slides
Person Detection with KWS: MultiTenancy Slides
MultiTenancy in TensorFlow Lite Micro Slides
Deploying the Pretrained Person Detection Model Reading
Deploying a Multi-Tenant Application Reading

§4.8 Gesture Recognition — Magic Wand

Topic Type
Recap: Time Series for Anomaly Detection Reading
TinyML Sensor Ecosystem Slides
Anatomy of an IMU Reading
Magic Wand Application Slides
Magic Wand Application Architecture Slides
Understanding the Magic Wand Application Reading
Deploying the Magic Wand Reading
Collecting Data for Your Custom Magic Wand Project Reading
Training and Deploying Your Custom Magic Wand Project Reading

§4.9 Responsible AI Deployment

Topic Type
Privacy Slides
Privacy Reading
Security Slides
Attacking a KWS Model in Colab Colab
Why do ML Models Fail after Deployment? Reading
Monitoring after Deployment Slides

§4.10 Summary

Topic Type
Congratulations! You Made it to the Finish Line! Slides
What Comes Next: Advanced Topics in TinyML Reading
What Do I Do Now? Slides
TinyMLx Project Extension (Optional) Reading
Note

These materials were originally developed for the HarvardX Professional Certificate in Tiny Machine Learning on edX. See the original curriculum for the full item-by-item breakdown including forum prompts and quizzes not listed above.

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