Isbn: 9798196773846 - pytorch deep learning blueprint: a hands-on guide to building, training, and deploying modern ai models with python, transformers, and llms (2026 edition) (6 resultados)

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  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798196773846

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    EUR 26,57

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798196773846

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    Condición: Nuevo

    EUR 25,46

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Amazon Digital Services LLC - Kdp Mai 2026, 2026

    9798196773846

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 32,64

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    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. Neuware - Can AI truly be trusted in the clinic In the high-stakes world of healthcare, 'close enough' isn't good enough.The gap between a Python script on a laptop and a deployed model in a hospital is a chasm filled with data silos, interoperability hurdles, and ethical minefields. Applied Clinical AI is the master blueprint for engineers and healthcare professionals who need to build, scale, and deploy AI that works in the real world.Authored by MOMENT TECH, this hands-on guide skips the hype and dives straight into the technical architecture required to modernize healthcare. From mastering the nuances of FHIR (Fast Healthcare Interoperability Resources) to fine-tuning LLMs for medical reasoning, this book provides the production-grade code and strategy needed for 2026 and beyond.Inside this comprehensive blueprint, you will master: The Modern Stack: Build robust clinical pipelines using Python, Transformers, and PyTorch.FHIR Integration: Bridge the gap between legacy EHR data and modern AI models with seamless interoperability.LLMs in Medicine: Go beyond generic prompts-learn to fine-tune Large Language Models for high-accuracy clinical decision support.Generative Healthcare: Implement VAEs, GANs, and Diffusion models for medical imaging and synthetic data generation.Production & Scale: Move from local training to distributed clusters with FSDP and high-performance deployment wrappers.The Ethics of Autonomy: Design agentic workflows that maintain 'Human-in-the-Loop' safety and HIPAA/GDPR compliance.Whether you are a senior software engineer moving into HealthTech or a clinical researcher looking to operationalize your models, this book is your technical North Star.Stop building prototypes. Start building the future of medicine.…

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798196773846

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    • Impresión bajo demanda

    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 26,21

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. Can AI truly be trusted in the clinic? In the high-stakes world of healthcare, "close enough" isn't good enough.The gap between a Python script on a laptop and a deployed model in a hospital is a chasm filled with data silos, interoperability hurdles, and ethical minefields. Applied Clinical AI is the master blueprint for engineers and healthcare professionals who need to build, scale, and deploy AI that works in the real world.Authored by MOMENT TECH, this hands-on guide skips the hype and dives straight into the technical architecture required to modernize healthcare. From mastering the nuances of FHIR (Fast Healthcare Interoperability Resources) to fine-tuning LLMs for medical reasoning, this book provides the production-grade code and strategy needed for 2026 and beyond.Inside this comprehensive blueprint, you will master: The Modern Stack: Build robust clinical pipelines using Python, Transformers, and PyTorch.FHIR Integration: Bridge the gap between legacy EHR data and modern AI models with seamless interoperability.LLMs in Medicine: Go beyond generic prompts-learn to fine-tune Large Language Models for high-accuracy clinical decision support.Generative Healthcare: Implement VAEs, GANs, and Diffusion models for medical imaging and synthetic data generation.Production & Scale: Move from local training to distributed clusters with FSDP and high-performance deployment wrappers.The Ethics of Autonomy: Design agentic workflows that maintain "Human-in-the-Loop" safety and HIPAA/GDPR compliance.Whether you are a senior software engineer moving into HealthTech or a clinical researcher looking to operationalize your models, this book is your technical North Star.Stop building prototypes. Start building the future of medicine. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Independently published, 2026

    9798196773846

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    • Impresión bajo demanda

    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

    Vendedor de 4 estrellas
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    Condición: Nuevo

    EUR 26,22

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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798196773846

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    • Impresión bajo demanda

    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 29,32

    Envío por EUR 43,02 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. Can AI truly be trusted in the clinic? In the high-stakes world of healthcare, "close enough" isn't good enough.The gap between a Python script on a laptop and a deployed model in a hospital is a chasm filled with data silos, interoperability hurdles, and ethical minefields. Applied Clinical AI is the master blueprint for engineers and healthcare professionals who need to build, scale, and deploy AI that works in the real world.Authored by MOMENT TECH, this hands-on guide skips the hype and dives straight into the technical architecture required to modernize healthcare. From mastering the nuances of FHIR (Fast Healthcare Interoperability Resources) to fine-tuning LLMs for medical reasoning, this book provides the production-grade code and strategy needed for 2026 and beyond.Inside this comprehensive blueprint, you will master: The Modern Stack: Build robust clinical pipelines using Python, Transformers, and PyTorch.FHIR Integration: Bridge the gap between legacy EHR data and modern AI models with seamless interoperability.LLMs in Medicine: Go beyond generic prompts-learn to fine-tune Large Language Models for high-accuracy clinical decision support.Generative Healthcare: Implement VAEs, GANs, and Diffusion models for medical imaging and synthetic data generation.Production & Scale: Move from local training to distributed clusters with FSDP and high-performance deployment wrappers.The Ethics of Autonomy: Design agentic workflows that maintain "Human-in-the-Loop" safety and HIPAA/GDPR compliance.Whether you are a senior software engineer moving into HealthTech or a clinical researcher looking to operationalize your models, this book is your technical North Star.Stop building prototypes. Start building the future of medicine. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…