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

Name: PyTorch AI Agent Engineering: Build Intelligent, Scalable Machine Learning Agents with Real-World Python Workflows and Modern Deep Learning Tools
Brand: Atlantic Books
SKU: 9798290123684
Price: 1948.0 INR
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by Jerry Caraballo

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ISBN13: 9798290123684
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: June 29, 2025
Pages: 168
Original Price: GBP 18.22
Language: English
Edition: N/A
Item Weight: 304 grams
BISAC Subject(s): Languages / Python

About The Book

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.

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