PyTorch AI Agent Engineering: Build Intelligent, Scalable Machine Learning Agents with Real-World Python Workflows and Modern Deep Learning Tools

By Jerry Caraballo

PyTorch AI Agent Engineering: Build Intelligent, Scalable Machine Learning Agents with Real-World Python Workflows and Modern Deep Learning Tools

PyTorch AI Agent Engineering is your essential guide to building robust, production-ready machine learning agents using modern Python workflows and cutting-edge deep learning tools. This hands-on book cuts through the noise and gives you practical, actionable strategies for every stage of agent development - from concept to deployment.

What sets this book apart?

End-to-End Engineering: Master every step, from designing minimal QA agents and building data pipelines, to packaging and deploying models with TorchScript, ONNX, and FastAPI.

Practical Agent Architecture: Learn how to construct modular, scalable agent systems using PyTorch, Lightning, Hydra, and the latest open-source frameworks.

Real-World Applications: Integrate classic ML with modern deep learning, deploy GANs for data augmentation, and orchestrate multi-agent pipelines for coding assistants, QA bots, and more.

Production-Ready Focus: Apply proven techniques for model versioning, reproducibility, security compliance (GDPR/CCPA), and automated CI/CD.

Performance and Reliability: Profile speed and memory, test for accuracy, and scale horizontally on Kubernetes - so your agents never hit a wall when it matters most.

Are you a developer, ML engineer, or data scientist eager to move beyond one-off demos? Do you want workflows that scale, adapt, and deliver results in real environments? This book is for you.

• Format: Paperback
• Language: English
• ISBN: B0FG28V559
• ISBN13: 9798290123684
• Release Date: June 2025
• Publisher: Independently Published
• Length: 168 Pages
• Weight: 0.67 lbs.
• Dimensions: 0.4" x 7.0" x 10.0"