Chevron Left
Retour à Introduction to Embedded Machine Learning

Avis et commentaires pour d'étudiants pour Introduction to Embedded Machine Learning par Edge Impulse

343 évaluations
83 avis

À propos du cours

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. This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those networks to microcontrollers, which is known as embedded machine learning or TinyML. You do not need any prior machine learning knowledge to take this course. Familiarity with Arduino and microcontrollers is advised to understand some topics as well as to tackle the projects. Some math (reading plots, arithmetic, algebra) is also required for quizzes and projects. We will cover the concepts and vocabulary necessary to understand the fundamentals of machine learning as well as provide demonstrations and projects to give you hands-on experience....

Meilleurs avis


23 sept. 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.


10 août 2021

As everybody says they go at a really fast pace, I had to watch like three times each video, but the content is really good and concise. Thanks to the sponsors and to the teacher

Filtrer par :

76 - 90 sur 90 Avis pour Introduction to Embedded Machine Learning

par Christos M

8 sept. 2021


par Jackline T

27 mars 2022

loved it

par Efraín A S

31 août 2021


par Vital P R

18 sept. 2021


par Rafael R P

8 nov. 2021

Rating: 3.5/5.0 Comments: It's a great course for a beginner in machine learning (4.5/5). If you already have some knowlogy in DSP (digital signal processing) and machine learning, this course is not for you. The Edge Impulse platform is good to present the main concepts of machine learning and to explain how to apply this concepts in real world. Like LEGO Mindstorm, I will recommend this course only for beginers. 

par Damião R

7 nov. 2021

This course is an excellent introduction to ML as a whole (specifically DNNs and CNNs), and embedded ML in particular. It makes use of Edge Impulse to abstract away a lot of details, while still giving us hands-on experience with the key aspects of an embedded ML project : feature engineering, model training and evaluation, as well as deployment on embedded systems.

par Robert B

6 avr. 2021

Interesting and useful projects to try out ML on embedded systems. I suspect it would be very challenging for people with no previous experience with ML, although embedded experience isn't really needed.

The host speaks very fast so may need to go back to listen again rather frequently.

par Aditya S

10 mai 2021

I did this course using phone, was really easy. Now, doing projects again using Arduino, was more engaging, ran into several installation issues, got them fixed one by one by looking at documentation, googling.

I would recommend to do this course by Arduino only for Embedded Developers.

par Jon H

10 juin 2021

A really good introduction to Embedded Machine Learning! Shows the basics of machine learning and teaches how to apply it yourself with only the need of your smartphone. Totally recommended!

par Ashish P

20 avr. 2022

i like the way course is designed.

i tried all project explained in course without re-viewing cource material.

par Gulshan J

15 févr. 2022

Excellent course, This course is beginner friendly and it helped me a lot in my projects.

par John C

12 mars 2021

Great course a lot of practical knowledge

par Joshua O

3 juin 2021

I love the course no doubt

par Szymon J

19 févr. 2021

Too many errors while installing Edge Impulse toolchain, otherwise good quality.


1 oct. 2021

very very bad