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Applied Machine Learning and AI Agents with PyTorch: From Fundamentals to Real-World Integration for Smarter Developer Productivity: 1 (The Robust Agent Series) - Softcover

 
9798293968510: Applied Machine Learning and AI Agents with PyTorch: From Fundamentals to Real-World Integration for Smarter Developer Productivity: 1 (The Robust Agent Series)

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Applied Machine Learning and AI Agents with PyTorch: From Fundamentals to Real-World Integration for Smarter Developer Productivity

Struggling to build intelligent, autonomous AI agents that actually deliver real-world impact? Applied Machine Learning and AI Agents with PyTorch offers the practical guidance and cutting-edge techniques you need to harness the full power of modern AI frameworks for smarter, more efficient developer workflows.

This comprehensive guide takes you from foundational machine learning concepts through advanced agent architectures, all grounded in PyTorch’s flexible, production-ready ecosystem. Whether you want to implement reinforcement learning, integrate vision and voice capabilities, or design multi-agent systems that collaborate and self-improve, this book equips you with actionable knowledge and ready-to-run code examples.

What will you gain?

  • Master PyTorch tooling and best practices tailored for AI agents

  • Build reinforcement learning models that solve real-world tasks efficiently

  • Design and deploy multi-modal agents combining text, images, and speech

  • Implement human-in-the-loop workflows and ethical guardrails for safer AI

  • Package, scale, and integrate agents seamlessly into development pipelines

  • Apply continuous feedback loops to refine and enhance agent performance

Are you ready to transform your AI projects from prototypes into scalable, reliable solutions? This book empowers developers, data scientists, and AI practitioners to create sophisticated AI agents that accelerate productivity and deliver measurable results.

Take the next step—equip yourself with the skills to build AI agents that work smarter and integrate seamlessly with your technology stack. This is your essential resource for applied AI development with PyTorch.

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Paperback. Zustand: new. Paperback. Applied Machine Learning and AI Agents with PyTorch: From Fundamentals to Real-World Integration for Smarter Developer Productivity Struggling to build intelligent, autonomous AI agents that actually deliver real-world impact? Applied Machine Learning and AI Agents with PyTorch offers the practical guidance and cutting-edge techniques you need to harness the full power of modern AI frameworks for smarter, more efficient developer workflows.This comprehensive guide takes you from foundational machine learning concepts through advanced agent architectures, all grounded in PyTorch's flexible, production-ready ecosystem. Whether you want to implement reinforcement learning, integrate vision and voice capabilities, or design multi-agent systems that collaborate and self-improve, this book equips you with actionable knowledge and ready-to-run code examples.What will you gain?Master PyTorch tooling and best practices tailored for AI agentsBuild reinforcement learning models that solve real-world tasks efficientlyDesign and deploy multi-modal agents combining text, images, and speechImplement human-in-the-loop workflows and ethical guardrails for safer AIPackage, scale, and integrate agents seamlessly into development pipelinesApply continuous feedback loops to refine and enhance agent performanceAre you ready to transform your AI projects from prototypes into scalable, reliable solutions? This book empowers developers, data scientists, and AI practitioners to create sophisticated AI agents that accelerate productivity and deliver measurable results.Take the next step-equip yourself with the skills to build AI agents that work smarter and integrate seamlessly with your technology stack. This is your essential resource for applied AI development with PyTorch. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798293968510

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