Machine learning (ML) allows us to teach computers to make predictions and decisions based on data and learn from experiences. In recent years, incredible optimizations have been made to machine learning algorithms, software frameworks, and embedded hardware. Thanks to this, running deep neural networks and other complex machine learning algorithms is possible on low-power devices like microcontrollers.
ofrecido por
Introduction to Embedded Machine Learning
Impulso EdgeAcerca de este Curso
53.846 vistas recientes
Fechas lÃmite flexibles
Restablece las fechas lÃmite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100Â % en lÃnea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Some math (reading plots, arithmetic, and algebra) is required in the course. Recommended to have experience with embedded systems (e.g. Arduino).
Aprox. 17 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
Qué aprenderás
The basics of a machine learning system
How to deploy a machine learning model to a microcontroller
How to use machine learning to make decisions and predictions in an embedded system
Habilidades que obtendrás
- Arduino
- Machine Learning
- Embedded System Design
- Microcontroller
- Computer Programming
Fechas lÃmite flexibles
Restablece las fechas lÃmite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100Â % en lÃnea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Some math (reading plots, arithmetic, and algebra) is required in the course. Recommended to have experience with embedded systems (e.g. Arduino).
Aprox. 17 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
ofrecido por
Impulso Edge
Edge Impulse is the leading development platform for machine learning on edge devices, free for developers and trusted by enterprises. Founded in 2019 by Zach Shelby and Jan Jongboom, we are on a mission to enable developers to create the next generation of intelligent devices. We believe that machine learning can enable positive change in society, and we are dedicated to support applications for good.
Programa - Qué aprenderás en este curso
6 horas para completar
Introduction to Machine Learning
In this module, we will introduce the concept of machine learning, how it can be used to solve problems, and its limitations. We will also cover how machine learning on embedded systems, such as single board computers and microcontrollers, can be effectively used to solve problems and create new types of computer interfaces. Then, we will introduce the Edge Impulse tool and collect motion data for a "magic wand" demo. Finally, we will examine the various features that can be calculated from this raw motion data, including root mean square (RMS), Fourier transform, and power spectral density (PSD).
6 horas para completar
13 videos (Total 107 minutos), 14 lecturas, 5 cuestionarios
6 horas para completar
Introduction to Neural Networks
In this module, we will look at how neural networks work, how to train them, and how to use them to perform inference in an embedded system. We will continue the previous demo of creating a motion classification system using motion data collected from a smartphone or Arduino board. Finally, we will challenge you with a new motion classification project where you will have the opportunity to implement the concepts learning in this module and the previous module.
6 horas para completar
10 videos (Total 77 minutos), 10 lecturas, 5 cuestionarios
6 horas para completar
Audio classification and Keyword Spotting
In this module, we cover audio classification on embedded systems. Specifically, we will go over the basics of extracting mel-frequency cepstral coefficients (MFCCs) as features from recorded audio, training a convolutional neural network (CNN) and deploying that neural network to a microcontroller. Additionally, we dive into some of the implementation strategies on embedded systems and talk about how machine learning compares to sensor fusion.
6 horas para completar
9 videos (Total 75 minutos), 7 lecturas, 4 cuestionarios
Reseñas
- 5 stars82,71Â %
- 4 stars15,42Â %
- 3 stars1,63Â %
- 1 star0,23Â %
Principales reseñas sobre INTRODUCTION TO EMBEDDED MACHINE LEARNING
por SA17 de feb. de 2021
ML on embedded systems is an exciting and growing technology and business domain. This course is a great place to start learning about it.
por MR11 de ago. de 2022
Great course for students interested in deploying machine learning models into embedded devices. Arduino module is not mandatory but will help alot fo doing more clomplex projects.
por SS23 de sep. de 2021
Thanks for detailed and well introduced topics, I enjoyed this course. I had prior knowledge in neural networks but this course was awsome for introducting ML for microcontrollers.
por TN14 de mar. de 2021
The videos and supplemental materials were well-presented and very useful. The hands-on projects were the best for learning practical use of the concepts.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si compro el Certificado?
¿Hay ayuda económica disponible?
Do I need to buy hardware to take this course?
What prior knowledge do I need?
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