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Design des maschinellen Lernsystems: mit End-to-End-Bei
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eBay-Artikelnr.:365732433771
Artikelmerkmale
- Artikelzustand
- ISBN-13
- 9781633438750
- Book Title
- Machine Learning System Design
- ISBN
- 9781633438750
Über dieses Produkt
Product Identifiers
Publisher
Manning Publications Co. LLC
ISBN-10
1633438759
ISBN-13
9781633438750
eBay Product ID (ePID)
25067498023
Product Key Features
Number of Pages
376 Pages
Publication Name
Machine Learning System Design : with End-To-End Examples
Language
English
Subject
Data Modeling & Design, General, Data Processing
Publication Year
2025
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback / Trade Paperback
Dimensions
Item Height
0.9 in
Item Weight
23.2 Oz
Item Length
9.2 in
Item Width
7.4 in
Additional Product Features
LCCN
2025-388480
Dewey Edition
23/eng/20250214
Illustrated
Yes
Dewey Decimal
006.3/1
Synopsis
Designing and delivering a machine learning system is an intricate multistep process that requires many skills and roles. Whether you're an engineer adding machine learning to an existing application or designing a ML system from the ground up, you need to navigate massive datasets and streams, lock down testing and deployment requirements, and master the unique complexities of putting ML models into production. That's where this book comes in. Machine Learning System Design shows you how to design and deploy a machine learning project from start to finish. You'll follow a step-by-step framework for designing, implementing, releasing, and maintaining ML systems. As you go, requirement checklists and real-world examples help you prepare to deliver and optimize your own ML systems. You'll especially love the campfire stories and personal tips, and ML system design interview tips. What's Inside, Metrics and evaluation criteria, Solve common dataset problems, Common pitfalls in ML system development, ML system design interview tips, For readers who know the basics of software engineering and machine learning. Examples in Python., Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems. From information gathering to release and maintenance, Machine Learning System Design guides you step-by-step through every stage of the machine learning process. Inside, you'll find a reliable framework for building, maintaining, and improving machine learning systems at any scale or complexity. In Machine Learning System Design: With end-to-end examples you will learn: * The big picture of machine learning system design * Analyzing a problem space to identify the optimal ML solution * Ace ML system design interviews * Selecting appropriate metrics and evaluation criteria * Prioritizing tasks at different stages of ML system design * Solving dataset-related problems with data gathering, error analysis, and feature engineering * Recognizing common pitfalls in ML system development * Designing ML systems to be lean, maintainable, and extensible over time Authors Valeri Babushkin and Arseny Kravchenko have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You'll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Designing and delivering a machine learning system is an intricate multistep process that requires many skills and roles. Whether you're an engineer adding machine learning to an existing application or designing a ML system from the ground up, you need to navigate massive datasets and streams, lock down testing and deployment requirements, and master the unique complexities of putting ML models into production. That's where this book comes in. About the book Machine Learning System Design shows you how to design and deploy a machine learning project from start to finish. You'll follow a step-by-step framework for designing, implementing, releasing, and maintaining ML systems. As you go, requirement checklists and real-world examples help you prepare to deliver and optimize your own ML systems. You'll especially love the campfire stories and personal tips, and ML system design interview tips. What's inside * Metrics and evaluation criteria * Solve common dataset problems * Common pitfalls in ML system development * ML system design interview tips About the reader For readers who know the basics of software engineering and machine learning. Examples in Python. About the author Valerii Babushkin is an accomplished data science leader with extensive experience. He currently serves as a Senior Principal at BP. Arseny Kravchenko is a seasoned ML engineer currently working as a Senior Staff Machine Learning Engineer at Instrumental. Table of Contents Part 1 1 Essentials of machine learning system design 2 Is there a problem? 3 Preliminary research 4 Design document Part 2 5 Loss functions and metrics 6 Gathering datasets 7 Validation schemas 8 Baseline solution Part 3 9 Error analysis 10 Training pipelines 11 Features and feature engineering 12 Measuring and reporting results Part 4 13 Integration 14 Monitoring and reliability 15 Serving and inference optimization 16 Ownership and maintenance, Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems.
LC Classification Number
Q325.5.B235 2025
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grandeagleretail
98,2% positive Bewertungen•2.8 Mio. Artikel verkauft
Angemeldet als gewerblicher Verkäufer
Verkäuferbewertungen (1'055'699)
- i***c (437)- Bewertung vom Käufer.Letzter MonatBestätigter KaufFast shipping. Item in excellent condition. Thank you!
- c***y (926)- Bewertung vom Käufer.Letzter MonatBestätigter KaufVery Sweet Book, Great Condition, appearance, quality and Value !
- 8***d (53)- Bewertung vom Käufer.Letzter MonatBestätigter KaufProduct arrived quickly and in the condition expected, as per their description. Great communication and I look forward to purchasing from them again!