SKU/Artículo: AMZ-B0G1MF239F
Applied Deep Learning and Edge AI with C++: Building Intelligent Systems for Vision, NLP, and Embedded Platforms (Machine Learning with Modern C++ Series)
Format:
Hardcover
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.53 kg
0.53 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Volume III – Applied Deep Learning and Edge AI with C++ Building Intelligent Systems for Vision, NLP, and Embedded PlatformsBring deep learning out of the cloud and into the real world. This volume is a hands-on guide to designing, optimizing, and deploying AI models on edge devices, embedded systems, and latency-critical environments.You’ll learn how to implement high-performance computer vision, natural language processing, and reinforcement learning pipelines using C++ and leading deployment frameworks—TensorRT, OpenVINO, CoreML, and ONNX Runtime. The book walks you through practical strategies for model quantization, hardware acceleration, memory optimization, and real-time inference on CPUs, GPUs, VPUs, and specialized accelerators.Through detailed case studies in autonomous systems, robotics, IoT, smart cameras, and embedded AI, you’ll gain the skills to build intelligent systems that are both computationally efficient and production-ready.Keywords: edge AI with C++, embedded machine learning, ONNX Runtime, TensorRT, computer vision, NLP, reinforcement learning, robotics, IoT, model quantization, hardware acceleration, real-time inference, edge deployment, optimized C++ AI.
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