Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Embedded Machine Learning in the Real World

tinyML via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore embedded machine learning applications in the real world through this insightful conference talk by Daniel Situnayake, Founding tinyML Engineer at Edge Impulse. Delve into the practical aspects of implementing machine learning on embedded devices, covering topics such as bandwidth, latency, and economics. Discover real-world use cases and gain an understanding of the current state-of-the-art in tiny models and accelerated hardware. Learn about the available tooling and explore future opportunities in this rapidly evolving field. Gain valuable insights into the challenges and potential of embedded machine learning from an industry expert.

Syllabus

Introduction
Overview
Bandwidth Latency Economics
Real World Use Cases
Practical State of the Art
Tiny Models
Accelerated Hardware
Tooling
Opportunities
Future
Outro

Taught by

tinyML

Reviews

Start your review of Embedded Machine Learning in the Real World

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.