Скачать или смотреть TinyML Hello World | Git Setup, Project Structure & Tensor Arena

In this video of the TinyML Hello World Series, we take the first steps into setting up the project environment and exploring how the model maps into code. This includes getting the TensorFlow Lite Micro sources, understanding the file structure, and defining memory for inference.

👉 What you’ll learn in this session:

Using Git & Make to download and build the TinyML Hello World code

Exploring the project file structure and its key components

Mapping the model into code with GetModel & version check

Defining the Tensor Arena as RAM space for tensors

Introduction to the Micro Test Framework Macros used in testing

This session shows how to prepare both the environment and the application code, laying the groundwork for running inference on embedded devices.

✍️ Prepared and Presented by Ramanan M

📚 Reference material:

Wes McKinney, Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, Second Edition, O’Reilly Media, 2018.

Chandra S.S., Vinod, Hareendran S., Anand, Machine Learning: A Practitioner’s Approach, PHI Learning Pvt. Ltd., 2021.

Pete Warden, Daniel Situnayake, TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers, O’Reilly Media, 2019.

🔖 Hashtags

#TinyML #HelloWorld #TensorFlowLite #ArduinoNano33BLE #EmbeddedAI #EdgeAI #MachineLearning #AIoT