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Rust for AI and Machine Learning: Build Faster, Safer, High-Performance Models with Practical Techniques for Training, Inference, and Deployment
Paperback
Publisher: Independently Published
Published: Dec 3 2025
Pages: 310
Weight: 1.19
Height: 0.65 Width: 7.00 Depth: 10.00
Language: English
Build Faster, Safer, High-Performance Models with Practical Techniques for Training, Inference, and Deployment
What if you could build AI systems that are faster, safer, and far more reliable than anything you've delivered before, without wrestling with runtime unpredictability or slow inference pipelines? As machine learning moves deeper into real-world applications, many teams are discovering that traditional tooling struggles to meet strict latency, security, and performance requirements.
This book shows exactly how Rust fits into today's ML ecosystem and how it can elevate your engineering capabilities. You'll learn through straightforward explanations, real code examples, and patterns used by production teams building high-performance AI systems right now.
In this book, you'll learn how to:
- Build efficient data-loading and preprocessing pipelines using Rust's memory safety and parallelism.
- Train both classical and deep-learning models using established Rust ML frameworks.
- Execute fast, stable inference with ONNX Runtime, tract, burn, and custom Rust implementations.
- Construct production-ready model-serving APIs with precise typing and efficient serialization.
- Combine Rust with Python, using PyO3 and maturin, to support hybrid research and deployment pipelines.
- Package Rust-based ML systems as binaries or containers for consistent deployment across platforms.
- Benchmark and optimize ML workloads using techniques that expose real bottlenecks and improve performance.
Ready to build AI systems that run faster, safer, and with higher performance? Get your copy today and start building with Rust.
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