Applied Edge AI: Deep Learning Outside of the Cloud
Applied Edge AI: Deep Learning Outside of the Cloud
Compared to Cloud Computing, which is centralized in computing and data storage, Edge Computing brings computation and data storage closer to data sources.
Edge AI combines edge computing and AI technology and has become a rapidly developing field in the past few years. Edge AI enables AI computing directly on the edge or client device, enhancing power efficiency, supporting low latency, and solving data privacy problems.
Therefore, what improvements need to be made to traditional deep learning algorithms in Edge AI scenarios? This course teaches you about deep model compression and optimization techniques, decentralized and collaborative deep learning approaches and algorithms, software, and hardware for Edge AI.
What will you learn?
- Summary of deep learning basics relevant for this course
- Deep model compression and optimization techniques
- Decentralized and collaborative deep learning
- Algorithms, software and hardware for Edge AI
Is this course for me?
Prerequisites
- High school math is required (pre-course)
- Basics in Machine Learning and Deep Learning
- Python as programming language
Duration: Not defined
Level: Advanced
Certification: Yes
Cost: Free
Language: English
Type: Self-Paced
Please note: these courses are provided by external sources, links are not actively managed or regularly updated, content might be moved or unavailable.
