Edge ML

Deploying and running machine learning models on edge devices like smartphones, IoT sensors, and embedded systems.

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Future-Proof

Why It Matters

Running AI at the edge enables real-time decisions without cloud latency, making engineers who can optimize and deploy models on constrained hardware essential for IoT, automotive, and mobile AI applications.

How to Get Started

Learn TensorFlow Lite or ONNX Runtime for mobile, deploy a model on an NVIDIA Jetson or Coral Edge TPU, and study model quantization and pruning techniques for edge deployment.

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