Model Serving with TensorFlow Lite focuses on deploying and running machine learning models efficiently on edge devices and mobile platforms. It enables organizations to deliver fast, lightweight, and optimized inference capabilities without relying on heavy cloud infrastructure. This training explains core concepts such as model conversion, quantization, and optimization techniques for mobile and embedded systems. It also covers on-device inference, performance tuning, memory optimization, and integration with Android, iOS, and IoT applications. You will learn how enterprises use TensorFlow Lite to deploy AI models for real-time predictions in resource-constrained environments. The course also highlights best practices for building efficient, scalable, and production-ready edge AI solutions.
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