What Does an E-Commerce Specialist Do?
September 19, 2024
Article
(11 reviews)
Recommended experience
Beginner level
For beginner AI developers, ML engineers, data scientists, and mobile developers looking to deploy optimized models on edge devices.
(11 reviews)
Recommended experience
Beginner level
For beginner AI developers, ML engineers, data scientists, and mobile developers looking to deploy optimized models on edge devices.
Learn to deploy AI models on edge devices like smartphones, using their local compute power for faster and more secure inference.
Explore converting PyTorch/TensorFlow models for device compatibility and quantize them for better performance and reduced model size.
Learn about device integration, including runtime dependencies, and how GPU, NPU, and CPU compute unit utilization affect performance.
Only available on desktop
As AI moves beyond the cloud, on-device inference is rapidly expanding to smartphones, IoT devices, robots, AR/VR headsets, and more. Billions of mobile and other edge devices are ready to run optimized AI models.
This course equips you with key skills to deploy AI on device: 1. Explore how deploying models on device reduces latency, enhances efficiency, and preserves privacy. 2. Go through key concepts of on-device deployment such as neural network graph capture, on-device compilation, and hardware acceleration. 3. Convert pretrained models from PyTorch and TensorFlow for on-device compatibility. 4. Deploy a real-time image segmentation model on device with just a few lines of code. 5. Test your model performance and validate numerical accuracy when deploying to on-device environments 6. Quantize and make your model up to 4x faster and 4x smaller for higher on-device performance. 7. See a demonstration of the steps for integrating the model into a functioning Android app. Learn from Krishna Sridhar, Senior Director of Engineering at Qualcomm, who has played a pivotal role in deploying over 1,000 models on devices and, with his team, has created the infrastructure used by over 100,000 applications. By learning these techniques, you’ll be positioned to develop and deploy AI to billions of devices and optimize your complex models to run efficiently on the edge.
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
11 reviews
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Reviewed on Jan 14, 2025
I'm not quite used to the Indian teacher's English accent, even though I know he is trying hard to impart knowledge.
DeepLearning.AI
Course
University of Illinois Urbana-Champaign
Course
Scrimba
Course
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