/FDP_tinyML

TinyML Workshop: Machine Learning on Raspberry Pi

Overview

Welcome to the tinyML Workshop! In this hands-on training, you'll learn how to leverage Edge Impulse for developing and deploying machine learning models on edge devices, with a specific focus on running models on a Raspberry Pi.

Prerequisites

Before you begin, ensure you have the following:

  • Laptop with a web browser
  • Edge Impulse account (sign up at Edge Impulse)
  • Raspberry Pi with Raspbian OS installed
  • Edge Impulse CLI installed on your development machine

Workshop Agenda

1. Introduction to Edge Impulse

  • Overview of Edge Impulse platform
  • Understanding the workflow: from data collection to model deployment
  • Edge Impulse Studio walkthrough

2. Data Collection and Preparation

  • Collecting sensor data using Edge Impulse mobile app or Rpi
  • Importing and visualizing data in Edge Impulse Studio
  • Data preprocessing and augmentation techniques

3. Building and Training a Machine Learning Model

  • Model selection and configuration
  • Training models using Edge Impulse Studio
  • Model evaluation and optimization

4. Deploying Models on Raspberry Pi

  • Introduction to Raspberry Pi deployment
  • Installing necessary dependencies on Raspberry Pi
  • Deploying and testing the trained model on Raspberry Pi

5. Real-world Use Cases

  • Showcase of real-world projects using Edge Impulse on Raspberry Pi
  • Discussion on potential applications and challenges

Getting Started

  1. Clone this repository:

    git clone https://github.com/a-1an/FDP_tinyML.git
cd FDP_tinyML

Resources

Happy learning, and enjoy the workshop!