Computer Vision with Embedded Machine Learning

via Coursera

Overview

Embark on a journey into the fascinating world of Computer Vision (CV) with our cutting-edge course designed to equip you with the skills to enable computers to perceive and interpret the world. This course, a collaborative effort by Edge Impulse, OpenMV, Seeed Studio, and the TinyML Foundation, dives deep into how deep learning and neural networks revolutionize image classification and object detection in both images and videos. Participants will explore the dynamic field of CV and learn how to harness machine learning (ML) algorithms and techniques for embedded systems, opening the doorway to embedded machine learning or TinyML.

Designed for individuals with a grounding in the Python programming language and basic ML concepts, including neural networks and the processes of training, inference, and evaluation, this course also necessitates a grasp of some mathematical concepts for quizzes and projects. It's highly recommended for newcomers to first complete the "Introduction to Embedded Machine Learning" course. Dive into the nitty-gritty of convolutional neural networks (CNNs), learn to classify images, detect objects, and get hands-on experience by training your own CNNs for deployment on microcontrollers or single board computers. This course is your gateway to mastering embedded ML applications, all made available through Coursera and categorized under Machine Learning Courses, Computer Vision Courses, and Embedded Systems Courses.