Ementorhub

What you'll learn

How to train and develop an image classification system using machine learning

How to train and develop an object detection system using machine learning

How to deploy a machine learning model to a microcontroller

Skills you'll gain

Embedded Systems

Deep Learning

Machine Learning

Data Collection

Data Ethics

Artificial Intelligence

Performance Testing

Image Analysis

Python Programming

Artificial Neural Networks

Computer Vision

There are 3 modules in this course

This course, offered by a partnership among Edge Impulse, OpenMV, Seeed Studio, and the TinyML Foundation, will give you an understanding of how deep learning with neural networks can be used to classify images and detect objects in images and videos. You will have the opportunity to deploy these machine learning models to embedded systems, which is known as embedded machine learning or TinyML. Familiarity with the Python programming language and basic ML concepts (such as neural networks, training, inference, and evaluation) is advised to understand some topics as well as complete the projects. Some math (reading plots, arithmetic, algebra) is also required for quizzes and projects. If you have not done so already, taking the "Introduction to Embedded Machine Learning" course is recommended. This course covers the concepts and vocabulary necessary to understand how convolutional neural networks (CNNs) operate, and it covers how to use them to classify images and detect objects. The hands-on projects will give you the opportunity to train your own CNNs and deploy them to a microcontroller and/or single board computer.

Convolutional Neural Networks

Object Detection