Edge AI and Edge Computer vision, Edge Computing, Artificial Intelligence, Tensorflow, Pytorch, Cloud Computing, ML
Sub Category
- Network & Security
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Objectives
- Understand the principles of Edge AI and its applications in real-world scenarios.
- Gain insights into Edge Computer Vision and its role in processing data at the edge.
- Identify the essential hardware components required for efficient edge computing.
- Evaluate hardware choices to optimize performance and power consumption for edge devices.
- Comprehend the fundamental concepts of Edge AI and Edge Computer Vision.
- Analyze the benefits, strategic implications, and challenges associated with implementing Edge AI solutions.
- Explore various software frameworks used for developing Edge AI applications.
- Learn how to select and leverage appropriate software tools for efficient edge computing.
- Master the deployment process of Edge AI models in real-world scenarios.
- Examine case studies to understand successful implementations and best practices in edge AI.
- Stay updated on the latest trends and innovations in the field of Edge AI.
- Anticipate future directions and potential advancements that will shape the landscape of edge computing.
Pre Requisites
- Basic Ides and Skills of AI (Artificial Intelligence)
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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