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{ "item_title" : "Advanced Deep Learning with Modern C++", "item_author" : [" Min Jae-Lin "], "item_description" : "Volume II - Advanced Deep Learning with Modern C++Architecting, Training, and Deploying Neural Systems with PyTorch C++, Flashlight, and ONNXMaster the cutting edge of high-performance deep learning engineering with Modern C++. This advanced volume takes you far beyond Python workflows, showing you how to design, optimize, and deploy neural systems directly in C++ using PyTorch's C++ API, Facebook's Flashlight framework, and ONNX Runtime.From classic architectures like CNNs and RNNs to state-of-the-art Transformers, you'll learn how to implement, train, and fine-tune models with full control over memory, performance, and execution. The book explores mixed-precision training, model quantization, distributed training strategies, and advanced optimization techniques tailored for production-grade systems.You'll also build complete inference pipelines, mastering ONNX export, runtime integration, CUDA acceleration, cuDNN optimizations, and TensorRT deployment for real-time, low-latency applications. Every chapter is designed to help experienced developers engineer deep learning systems that are fast, scalable, and production ready.Keywords: deep learning with C++, PyTorch C++ frontend, neural network engineering, ONNX Runtime, Flashlight AI, CUDA optimization, Transformer models, CNNs, RNNs, model quantization, TensorRT deployment, GPU computing, high-performance AI systems.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/827/385/9798273859401_b.jpg", "price_data" : { "retail_price" : "16.00", "online_price" : "16.00", "our_price" : "16.00", "club_price" : "16.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advanced Deep Learning with Modern C++|Min Jae-Lin

Advanced Deep Learning with Modern C++ : Architecting, Training, and Deploying Neural Systems Using PyTorch C++, Flashlight, and ONNX

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Overview

Volume II - Advanced Deep Learning with Modern C++
Architecting, Training, and Deploying Neural Systems with PyTorch C++, Flashlight, and ONNX

Master the cutting edge of high-performance deep learning engineering with Modern C++. This advanced volume takes you far beyond Python workflows, showing you how to design, optimize, and deploy neural systems directly in C++ using PyTorch's C++ API, Facebook's Flashlight framework, and ONNX Runtime.

From classic architectures like CNNs and RNNs to state-of-the-art Transformers, you'll learn how to implement, train, and fine-tune models with full control over memory, performance, and execution. The book explores mixed-precision training, model quantization, distributed training strategies, and advanced optimization techniques tailored for production-grade systems.

You'll also build complete inference pipelines, mastering ONNX export, runtime integration, CUDA acceleration, cuDNN optimizations, and TensorRT deployment for real-time, low-latency applications. Every chapter is designed to help experienced developers engineer deep learning systems that are fast, scalable, and production ready.

Keywords: deep learning with C++, PyTorch C++ frontend, neural network engineering, ONNX Runtime, Flashlight AI, CUDA optimization, Transformer models, CNNs, RNNs, model quantization, TensorRT deployment, GPU computing, high-performance AI systems.

This item is Non-Returnable

Details

  • ISBN-13: 9798273859401
  • ISBN-10: 9798273859401
  • Publisher: Independently Published
  • Publish Date: November 2025
  • Dimensions: 10 x 7 x 0.44 inches
  • Shipping Weight: 0.81 pounds
  • Page Count: 208

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