Вернуться к Computer Vision with Embedded Machine Learning
Отзывы учащихся о курсе Computer Vision with Embedded Machine Learning от партнера Edge Impulse
Оценки: 13
О курсе
Computer vision (CV) is a fascinating field of study that attempts to automate the process of assigning meaning to digital images or videos. In other words, we are helping computers see and understand the world around us! A number of machine learning (ML) algorithms and techniques can be used to accomplish CV tasks, and as ML becomes faster and more efficient, we can deploy these techniques to embedded systems.
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.
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1–3 из 3 отзывов о курсе Computer Vision with Embedded Machine Learning
автор: Michal L
•24 сент. 2021 г.
Great course, Shawn always explains things in a clear and engaging way, with a strong focus on the application of the concepts. I'm definitely looking forward to more courses on embedded ML!
автор: Julian L
•24 сент. 2021 г.
It´s a great Course . Thanks
автор: Ralph Y
•24 окт. 2021 г.
Helped understand new concepts
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