Isbn: 9798901120835 - debugging intelligence: fixing machine learning models (4 risultati)

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  • Lingua: Inglese

    Editore: Notion Press Media Pvt. Ltd, 2025

    9798901120835

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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

  • Lingua: Inglese

    Editore: Notion Press Media Pvt. Ltd, 2025

    9798901120835

    • Brossura

    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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

  • Lingua: Inglese

    Editore: Notion Press Media Pvt. Ltd Okt 2025, 2025

    9798901120835

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

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    Taschenbuch. Condizione: Neu. Neuware - The journey of this book has shown that debugging in machine learning is far more than a technical afterthought, it is a discipline in itself. Debugging is not simply the process of fixing broken code but the deeper act of uncovering why machine learning models fail, understanding the roots of those failures, and ensuring systems behave reliably in the environments where they operate. Machine learning models are built upon layers of design decisions, data assumptions, and performance trade-offs. By the time a system reaches production, it carries with it both the strengths and the hidden weaknesses of those choices. Debugging is the practice of interrogating those assumptions, shining light on vulnerabilities, and building confidence that the system will perform as intended in the real world.…

  • Lingua: Inglese

    Editore: Notion Press, 2025

    9798901120835

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    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Paperback. Condizione: new. Paperback. The journey of this book has shown that debugging in machine learning is far more than a technical afterthought, it is a discipline in itself. Debugging is not simply the process of fixing broken code but the deeper act of uncovering why machine learning models fail, understanding the roots of those failures, and ensuring systems behave reliably in the environments where they operate. Machine learning models are built upon layers of design decisions, data assumptions, and performance trade-offs. By the time a system reaches production, it carries with it both the strengths and the hidden weaknesses of those choices. Debugging is the practice of interrogating those assumptions, shining light on vulnerabilities, and building confidence that the system will perform as intended in the real world. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…