Designing machine learning systems : an iterative process for production-ready applications /

"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holisti...

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Detaylı Bibliyografya
Yazar: Huyen, Chip (Yazar)
Materyal Türü: Kitap
Dil:English
Baskı/Yayın Bilgisi: Navi Mumbai : Sebastopol, CA : Shroff Publishers and Distributors ; O'Reilly Media, c2022 [reprinted 2025].
Konular:
Classic Catalogue: View this record in Classic Catalogue
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245 1 0 |a Designing machine learning systems :  |b an iterative process for production-ready applications /  |c Chip Huyen. 
246 3 8 |a Designing machine learning systems 
260 |a Navi Mumbai :  |b Shroff Publishers and Distributors ;  |a Sebastopol, CA :  |b O'Reilly Media,  |c c2022 [reprinted 2025]. 
300 |a xvi, 367 pages :  |b illustrations ;  |c 24 cm 
500 |a First edition : May 2022 
504 |a Includes bibliographical references and index. 
505 0 0 |t Overview of machine learning systems --  |t Introduction to machine learning systems design --  |t Data engineering fundamentals --  |t Training data --  |t Feature Engineering --  |t Model development and offline evaluation --  |t Model develoypment and prediction service --  |t Data distribution shifts and monitoring --  |t Continual learning and test in production --  |t Infrastructure and tooling for MLOps --  |t The human side of machine learning 
520 |a "Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references."--Amazon.com. 
526 |a CSE  |x Annajiat Alim Rasel Senior Lecturer Department of Computer Science and Engineering BRAC University Course Type : General 
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