Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
genuine image
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements.
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
商品＃: 51479271

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

回答者の88%がこの商品を友人に勧めたいと回答

商品＃: 51479271

JPY 8770

JPY 13938

価格の詳細

配送料と関税を除く ( 配送料と関税は購入手続き時に計算されます )

*すべての商品はアメリカから輸入されます

37%

在庫あり
アメリカ USA ストアからの輸入品
今すぐ注文すると 頃に届きます 水曜日, 9月 09
安全な取引安全な取引

Ubuyはお客様のセキュリティとプライバシーの保護に努めています。当社の高度な決済セキュリティシステムは、AES（高度暗号化標準）およびSSL（セキュアソケットレイヤー）プロトコルを使用して送信中の情報を暗号化することで機密性を確保しています。お客様の決済情報は第三者の販売者と共有されることはなく、100%安全に保護されています。

最高の物流パートナー
  • fedex
  • dhl
Learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements.
もっと見る
U-Care保証：
なし
プランを選択してください
fast shipping

Fast
Shipping

free return

Free
Return*

安全な梱包

安全な梱包

100％正規品

100％正規品

pci-dss

PCI DSS 準拠

iso certified

ISO 27001認証取得

paypal payment
visa payment
mastercard payment
american express payment
jcb payment

この商品の利点

Iterative Approach
Emphasizes an iterative process that allows developers to refine machine learning models continuously, ensuring more robust and scalable applications suitable for production environments.
Practical Guidance
Offers step-by-step guidance and real-world scenarios that help practitioners effectively apply machine learning principles, bridging the gap between theory and practical implementation.
Comprehensive Coverage
Covers a wide range of topics in machine learning system design, making it a valuable resource for both novices and experienced professionals looking to enhance their skill set.

製品詳細

Explore the iterative process of building production-ready machine learning applications. Get the 1st Edition now at Ubuy KW, your 日本 for all your shopping needs.
  • Provides a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements
  • Addresses scenarios such as engineering data, automating model development, developing a monitoring system, architecting an ML platform, and developing responsible ML systems
  • Geared towards ML engineers, data scientists, data engineers, ML platform engineers, and engineering managers
  • Not an introduction to ML, assumes readers have a basic understanding of ML models, techniques, metrics, statistical concepts, and common ML tasks
  • Intended for individuals wanting to leverage ML to solve real-world problems, including technical and business leaders considering adopting ML solutions
  • Includes ample case studies and references, not a tutorial book with extensive code snippets
Publisher O'Reilly Media
Publication date June 21, 2022
Edition 1st
Language English
Print length 386 pages
ISBN-10 1098107969
ISBN-13 978-1098107963
Item Weight 1.4 pounds (640 grams)
Dimensions 6.9 x 0.7 x 9.1 inches (17.5 x 1.8 x 23.1 cm)

どんな人にお勧めですか？

Suitable For
  • Data Scientists

    Ideal for data scientists seeking practical frameworks for developing and deploying scalable machine learning systems effectively.

  • Software Engineers

    Provides software engineers with guidelines for integrating machine learning into existing applications and enhancing production readiness.

  • Project Managers

    Useful for project managers overseeing machine learning projects, ensuring alignment between development and operational goals.

Not Suitable For
  • Complete Beginners

    Not suitable for total newcomers; prior knowledge of machine learning principles is necessary to grasp the content.

製品説明書

何か質問はありますか？ チャットでお問い合わせください

お客様の質問と回答

  • 質問: What is the main focus of 'Designing Machine Learning Systems'?

    回答: The main focus of 'Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications' is to guide practitioners through the iterative processes required to build effective machine learning systems. It delves into the methodologies for designing, developing, and deploying systems that are not only robust but also scalable. This book emphasizes understanding user needs and iterating based on feedback, making it integral for those looking to implement practical machine learning solutions in various fields, such as finance, healthcare, or retail.
  • 質問: Who is the target audience for this book?

    回答: 'Designing Machine Learning Systems' is primarily aimed at software engineers, data scientists, and machine learning practitioners who seek practical guidance on building production-ready systems. Additionally, it appeals to product managers and decision-makers who want to comprehend the iterative design process. The book serves as an essential resource for anyone involved in delivering AI-driven solutions, ensuring they can navigate the complexities of machine learning methodologies effectively.
  • 質問: Does the book cover real-world case studies?

    回答: Yes, the book incorporates various real-world case studies to illustrate the concepts discussed. These examples demonstrate how the iterative process can be applied to actual machine learning projects, including challenges faced and solutions implemented. By studying these cases, readers can gain valuable insights into best practices and common pitfalls, which can help them implement similar strategies in their own projects across industries such as e-commerce and healthcare.
  • 質問: What methodologies are discussed in the book?

    回答: The book discusses several methodologies including agile development, user-centered design, and model prototyping. Each methodology is presented in the context of machine learning, focusing on how they can be utilized to enhance system design and user experience. By understanding these methodologies, practitioners can better manage project timelines and improve collaboration among team members in dynamic environments, leading to more effective and user-oriented machine learning systems.
  • 質問: How does this book address challenges in machine learning system design?

    回答: This book addresses challenges in machine learning system design by focusing on common pitfalls and providing targeted solutions. It highlights the importance of validation, data management, and feedback loops in overcoming these challenges. Readers will learn about iterative testing and refinement strategies that can be applied to tackle issues such as model drift or data quality, ensuring that their systems remain effective and reliable in production environments.
  • 質問: Is there any accompanying online resource or community for readers?

    回答: Yes, many readers have access to online resources and communities related to the book. These platforms often include discussion forums, supplementary materials, and practical exercises. Engaging with these resources not only enhances the learning experience but also allows readers to connect with like-minded individuals. This collaborative learning approach fosters an environment where they can share insights and challenges faced while applying the concepts from the book in real-world scenarios.
  • 質問: Are there any prerequisites for understanding the content?

    回答: While it's beneficial to have a basic understanding of machine learning concepts, the book is structured to cater to both novices and experienced practitioners. Readers should ideally be familiar with programming and statistical principles, but the content gradually builds up, ensuring that those with varying levels of expertise can grasp key ideas. This inclusivity makes it an excellent resource for teams looking to upskill or for individuals aiming to enter the field of machine learning.
  • 質問: What makes this book different from other machine learning books?

    回答: What sets 'Designing Machine Learning Systems' apart from other machine learning books is its strong emphasis on the iterative process and practical application in real-world scenarios. Rather than focusing solely on theory, it combines theoretical principles with actionable steps, making it easier for readers to implement the strategies in their projects. This pragmatic approach ensures that the reader not only learns about machine learning but is also equipped with the tools needed for successful application.
  • 質問: Where can I buy 'Designing Machine Learning Systems' in NG?

    回答: You can purchase 'Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications 1st Edition' at Ubuy, a reliable online retailer in Japan. Ubuy offers a user-friendly platform that allows you to browse, order, and have the book delivered to your doorstep. With Ubuy, you are guaranteed a smooth shopping experience with secure payment options and efficient customer support, ensuring you can easily access this essential resource for your machine learning journey.

Intelligence & Semantics Editorial Review

  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本
  • ubuy 日本

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications is authored by Chip Huyen and published by O'Reilly Media. This book serves as an essential guide for practitioners aiming to transition machine learning from research to real-world applications. Its focus on iterative processes, along with a clear writing style, allows readers to grasp complex concepts surrounding data-centric AI, model deployment, and monitoring efficiently. Featuring real-world case studies and practical examples, Huyen provides insights into productionizing ML systems that are valuable for engineers, researchers, and data scientists alike. The structured approach makes this resource particularly beneficial for those mentoring others in the field.

お客様のレビュー＆評価

994 カスタマー評価
  • 5 星
    80%
  • 4 星
    10%
  • 3 星
    5%
  • 2 星
    2%
  • 1 星
    3%

この商品のレビュー

お考えをお聞かせください

長所

  • Comprehensive overview of machine learning implementation
  • Clear explanations of complex concepts
  • Real-world case studies make learning relatable
  • Great resource for mentoring undergrad students
  • Structured for both practitioners and leaders

短所

  • Some topics may not delve deeply into details

プラットフォームの信頼性とお客様の安心

trustpilot logo
4.2/5 9250 + レビュー
レビューを読む
MA
Mohammad
Verified buyer

“Excellent quality and original too,when ubuy send original things I will appreciate that ,I very satisfied thank you”

23 July 2026 · via Trustpilot
CK
Chitra
Verified buyer

“The order and delivery progress was communicated very well. Package arrived within the estimated time. Products arrived as expected in good condition.”

22-Jul-26 · via Trustpilot
K
kund
Verified buyer

“Good supply of products. Safe payment methods, and shipment worldwide! Genuine products.”

23-Jul-26 · via Trustpilot
OO
Onesi
Verified buyer

“Was my first time buying a product from Ubuy, but I found it so helpful. This is reliable. Gonna place a new order!”

22 July 2026 · via Trustpilot
SJ
SAO JOHN
Verified buyer

“Ubuy is a great online platform to buy stuff. Reliable, fast delivery time and great value for money. I've been using Ubuy online shopping platform for three years now and will continue to do so.”

23 July 2026 · via Trustpilot
安全な決済 国際配送 簡単返品 正規品保証

価格推移

重要な情報

  • 注意：国際運送の商品に関して、製造会社保障は無効になる可能性、アフターサービスは受けれない可能性、取説や安全情報は発送先の言語になっていない可能性ある。商品とその付属品は配送先の国の規格、仕様、ラベル表示法などに適応していない可能性があります。また、配送先の国の電力企画に適応しいない（アダプタや変換器を必要とする）可能性があります。ご注文の商品は配送先の国に輸入することは合法なのかを確認するのは購入者の責任になります。Ubuyからご購入の際、受け取り者は正式な輸入者となり、配送先の全ての法律やルールに遵守する必要があります。
  • Ubuyはグローバル検索エンジンのためリストにある全ての商品が購入できないことがあります。商品は輸出規制、貿易規制があります。

JPY 8770

JPY 13938

今すぐ注文すると 頃に届きます 水曜日, 9月 09

数量：

安全な取引安全な取引

PCI DSS準拠・ISO 27001:2022認証取得。すべてのご注文に暗号化決済と充実したバイヤープロテクションが適用されます。

最高の物流パートナー
  • fedex
  • dhl
最速の国際配送

特徴と利点

  • Design ML systems that are reliable and adaptable
  • Learn to process and create training data
  • Automate the process for continually developing, evaluating, deploying, and updating models
  • Develop a monitoring system to detect and address production issues
  • Architect an ML platform that serves across use cases
  • Develop responsible ML systems

Ubuyの安心保証

100％正規品、PCI DSS準拠の決済セキュリティ、ISO 27001認証のデータ保護、最速の国際配送、無料返品※、安全な梱包をすべてのご注文でお届けします。