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In Designing Machine Learning Systems, Chip Huyen presents a comprehensive guide that delves deep into the intricacies of creating effective machine learning systems. This book is not just a technical manual; it embodies a holistic approach that covers the essential aspects of reliability, scalability, maintainability, and adaptability in an ever-evolving technological landscape.
Huyen walks readers through the essential phases of system design, emphasising the importance of understanding the entire lifecycle of machine learning models. The narrative is rich with practical examples and case studies that illustrate how theoretical concepts translate into real-world applications. Readers will learn how to approach challenges systematically, ensuring that their systems not only meet current demands but are also prepared for future shifts in business requirements.
This book is ideal for data scientists, machine learning engineers, and anyone interested in the design and implementation of machine learning systems. It serves as a robust reference for those who may have previously read Huyen's other works, such as Building Machine Learning Powered Applications, and are now looking to deepen their understanding of system design.
“A must-read for anyone serious about building effective machine learning systems.”
Format: Paperback / softback
Dimensions: × ×
Pages: 360
Publisher: O'Reilly Media
ISBN: 9781098107963
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