Production Onnx: Model Conversion, Runtime Optimization, Hardware Acceleration, and AI Deployment

By Zyren Aurev

MASTER ONNX AND BUILD PRODUCTION-READY AI INFERENCE SYSTEMS.

Machine learning does not end with model training. To use an AI model in the real world, you need reliable model conversion, optimized inference, hardware acceleration, scalable deployment, and production monitoring.

PRODUCTION ONNX: Model Conversion, Runtime Optimization, Hardware Acceleration, and AI Deployment is a practical technical guide to ONNX and ONNX Runtime, designed for developers, AI engineers, machine-learning engineers, and MLOps practitioners who want to move models from development into production.

Inside, you'll learn how to:

Understand ONNX models, tensors, operators, and computational graphs

Convert PyTorch and other machine-learning models to ONNX

Validate and troubleshoot ONNX model conversion

Optimize ONNX graphs and improve AI inference performance

Apply quantization, INT8, FP16, and reduced-precision inference

Accelerate inference with CUDA, NVIDIA GPUs, TensorRT, OpenVINO, DirectML, and other execution providers

Build efficient ONNX Runtime inference pipelines and APIs

Deploy AI inference services using Docker, Kubernetes, and cloud infrastructure

Improve throughput with batching, concurrency, scheduling, and horizontal scaling

Implement monitoring, logging, tracing, metrics, and AI observability

Secure ONNX models, inference APIs, and production deployments

Perform advanced ONNX Runtime performance tuning and optimization

Build cross-platform ONNX deployment and optimization pipelines

Manage model versions, rollouts, rollbacks, testing, and production reliability

Balance inference speed, model accuracy, infrastructure cost, and maintainability

From ONNX model conversion and runtime optimization to GPU acceleration, AI deployment, MLOps, and production inference, this book provides a complete path for turning trained machine-learning models into reliable production systems.

If you want to understand ONNX, ONNX Runtime, model optimization, quantization, hardware acceleration, and scalable AI inference, PRODUCTION ONNX gives you the practical foundation to build and operate modern machine-learning inference systems.

Convert. Optimize. Accelerate. Deploy.

• Format: Paperback
• Language: English
• ISBN: B0HHBDQXBN
• ISBN13: 9798171013226
• Release Date: August 2026
• Publisher: Independently Published
• Length: 320 Pages
• Weight: 1.64 lbs.
• Dimensions: 0.7" x 8.5" x 11.0"