Tomak kerem (42 risultati)

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  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404452 / 9781591404453

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  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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  • Lingua: Inglese

    Editore: O'Reilly, 2026

    9798341643185

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

  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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  • Lingua: Inglese

    Editore: O'Reilly, 2026

    9798341643185

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  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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    Da: California Books, Miami, FL, U.S.A.California Books

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  • Lingua: Inglese

    Editore: O'Reilly Media, US, 2026

    9798341643185

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    Da: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA

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    EUR 63,00

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    Paperback. Condizione: New. Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation.Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge.Build AutoML pipelines for tabular, text, image, and time series dataDeploy models with fast, scalable workflows using MLOps best practicesCompare and navigate today's leading AutoML platformsInterpret model results and make informed decisions with explainability toolsExplore how AutoML leads into next-gen agentic AI systems.

  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Da: California Books, Miami, FL, U.S.A.California Books

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  • Lingua: Inglese

    Editore: O′Reilly, 2026

    9798341643185

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    EUR 55,92

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  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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    EUR 51,50

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  • Lingua: Inglese

    Editore: O'Reilly Media, US, 2026

    9798341643185

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    Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA

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    Paperback. Condizione: New. Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation.Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge.Build AutoML pipelines for tabular, text, image, and time series dataDeploy models with fast, scalable workflows using MLOps best practicesCompare and navigate today's leading AutoML platformsInterpret model results and make informed decisions with explainability toolsExplore how AutoML leads into next-gen agentic AI systems.

  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    EUR 81,21

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  • Editore: O'Reilly Media, 2026

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    Condizione: Usato - Molto buono

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    paperback. Condizione: Very Good.

  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices

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  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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    Da: Speedyhen, Hertfordshire, Regno UnitoSpeedyhen

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  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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  • Lingua: Inglese

    Editore: O'reilly Media Apr 2026, 2026

    9798341643185

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    Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, GermaniaRheinberg-Buch Andreas Meier eK

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    EUR 80,00

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    Taschenbuch. Condizione: Neu. Neuware -Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. - Build AutoML pipelines for tabular, text, image, and time series data - Deploy models with fast, scalable workflows using MLOps best practices - Compare and navigate today's leading AutoML platforms - Interpret model results and make informed decisions with explainability tools - Explore how AutoML leads into next-gen agentic AI systems 400 pp. Englisch.

  • Lingua: Inglese

    Editore: O'reilly Media Apr 2026, 2026

    9798341643185

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. Neuware -Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. - Build AutoML pipelines for tabular, text, image, and time series data - Deploy models with fast, scalable workflows using MLOps best practices - Compare and navigate today's leading AutoML platforms - Interpret model results and make informed decisions with explainability tools - Explore how AutoML leads into next-gen agentic AI systems 400 pp. Englisch.

  • Lingua: Inglese

    Editore: O'reilly Media Apr 2026, 2026

    9798341643185

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    Da: Wegmann1855, Zwiesel, GermaniaWegmann1855

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    Taschenbuch. Condizione: Neu. Neuware -Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. - Build AutoML pipelines for tabular, text, image, and time series data - Deploy models with fast, scalable workflows using MLOps best practices - Compare and navigate today's leading AutoML platforms - Interpret model results and make informed decisions with explainability tools - Explore how AutoML leads into next-gen agentic AI systems.

  • Lingua: Inglese

    Editore: O'Reilly Media, US, 2026

    9798341643185

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    Paperback. Condizione: New. Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation.Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge.Build AutoML pipelines for tabular, text, image, and time series dataDeploy models with fast, scalable workflows using MLOps best practicesCompare and navigate today's leading AutoML platformsInterpret model results and make informed decisions with explainability toolsExplore how AutoML leads into next-gen agentic AI systems.

  • Lingua: Inglese

    Editore: O'Reilly Media, 2026

    9798341643185

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    Da: moluna, Greven, Germaniamoluna

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  • Lingua: Inglese

    Editore: IGI Global, US, 2004

    1591404444 / 9781591404446

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    Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA

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    Hardback. Condizione: New.

  • Lingua: Inglese

    Editore: Igi Global, 2004

    1591404444 / 9781591404446

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    Condizione: As New. Unread book in perfect condition.

  • Lingua: Inglese

    Editore: O'reilly Media Apr 2026, 2026

    9798341643185

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Neuware - Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. - Build AutoML pipelines for tabular, text, image, and time series data - Deploy models with fast, scalable workflows using MLOps best practices - Compare and navigate today's leading AutoML platforms - Interpret model results and make informed decisions with explainability tools - Explore how AutoML leads into next-gen agentic AI systems.

  • Lingua: Inglese

    Editore: O'Reilly Media, Sebastopol, 2026

    9798341643185

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    Paperback. Condizione: new. Paperback. Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation.Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge.Build AutoML pipelines for tabular, text, image, and time series dataDeploy models with fast, scalable workflows using MLOps best practicesCompare and navigate today's leading AutoML platformsInterpret model results and make informed decisions with explainability toolsExplore how AutoML leads into next-gen agentic AI systems Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Lingua: Inglese

    Editore: O'reilly Media Apr 2026, 2026

    9798341643185

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. Neuware -Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation. Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge. - Build AutoML pipelines for tabular, text, image, and time series data - Deploy models with fast, scalable workflows using MLOps best practices - Compare and navigate today's leading AutoML platforms - Interpret model results and make informed decisions with explainability tools - Explore how AutoML leads into next-gen agentic AI systemsLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 400 pp. Englisch.

  • Lingua: Inglese

    Editore: O'Reilly Media, US, 2026

    9798341643185

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    Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK

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    Paperback. Condizione: New. Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'll learn how to build, evaluate, and deploy AutoML models that reduce complexity and accelerate innovation.Author Kerem Tomak shares insights on how to integrate models into end-to-end deployment workflows using popular tools like Kubeflow, MLflow, and Airflow, while exploring cross-platform approaches with Vertex AI, SageMaker Autopilot, Azure AutoML, Auto-sklearn, and H2O.ai. Real-world case studies highlight applications across finance, healthcare, and retail, while chapters on ethics, governance, and agentic AI help future-proof your knowledge.Build AutoML pipelines for tabular, text, image, and time series dataDeploy models with fast, scalable workflows using MLOps best practicesCompare and navigate today's leading AutoML platformsInterpret model results and make informed decisions with explainability toolsExplore how AutoML leads into next-gen agentic AI systems.