Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications, (Paperback)
Learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments.
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications, (Paperback)
Προϊόν #: 57403947

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications, (Paperback)

Προϊόν #: 57403947

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Learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments.
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What Stands Out

Iterative Approach
Offers a step-by-step guide that emphasizes the iterative nature of developing machine learning systems, ensuring a practical framework for building production-ready applications.
Comprehensive Coverage
Covers a wide array of topics, from initial design to deployment, making it suitable for both beginners and experienced practitioners looking for in-depth knowledge.
Real-World Examples
Includes case studies and real-world applications that illustrate best practices in machine learning, enhancing the reader's ability to apply concepts to their own projects.

Λεπτομέρειες προιόντος

Shop Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications, (Paperback) online at a best price in Greece. 276053840
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateJune, 2022
Pages386
Reading levelProfessional and Scholarly
SubgenreData Science
Series titleNo Series
Edition1
PublisherO'Reilly Media
Original languagesEnglish
LanguageEnglish
Is collectibleN
EditorVaishali V Phalke, Mohannad Ibrahim, Douglas J Quint, Hemant Parmar, Gaurang Shah, Sachin Gujar
Recording time0 min
Retail packagingSingle Piece
Assembled product dimensions (l x w x h)6.90 x 0.70 x 9.10 in (17.5 x 1.8 x 23.1 cm)
Assembled product weight1.35 lb (610 grams)
Bisac subject headingComputers

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Provides foundational knowledge and practical steps to develop machine learning applications effectively.

  • Tech Professionals

    Ideal for software engineers seeking to incorporate machine learning into existing systems in a structured manner.

  • Project Managers

    Useful for overseeing machine learning projects with a strong focus on iterative improvement and production readiness.

Not Suitable For
  • Beginners in ML

    May be too advanced for those without prior knowledge of machine learning or programming concepts.

ΠΕΡΙΓΡΑΦΗ ΤΟΥ ΠΡΟΪΟΝΤΟΣ

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications, (Paperback)

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Ερωτήσεις & Απαντήσεις Πελατών

  • ερώτηση: What is the primary focus of this book?

    απάντηση: The book focuses on designing reliable, scalable, and maintainable machine learning systems adapted to changing environments.
  • ερώτηση: Are there real-life examples included in the book?

    απάντηση: Yes, the book includes actual case studies to illustrate the iterative design framework.
  • ερώτηση: Who is the author of this book?

    απάντηση: The author is Chip Huyen, co-founder of Claypot AI.

Chip Huyen All Books Editorial Review

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications is a comprehensive paperback guide published by O'Reilly Media in June 2022. With 386 pages dedicated to the field of computing and internet, this non-fiction resource is ideal for professionals and scholars interested in data science. The editors, including experts such as Vaishali V Phalke and Mohannad Ibrahim, ensure that the content is both authoritative and practical. This book focuses on the iterative process essential for designing robust machine learning systems, making it a vital read for anyone looking to enhance their skills in this rapidly evolving field.

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Πλεονεκτήματα

  • Ideal for professionals and scholars in data science
  • Comprehensive coverage of machine learning design
  • Contributions from multiple expert editors
  • Focused on production-ready applications
  • Clear and structured iterative process

Μειονεκτήματα

  • May not suit casual readers or beginners

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