Machine learning system design : with end-to-end examples /

"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 st...

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Bibliographic Details
Main Authors: Babushkin, Valerii (Author), Kravchenko, Arseny (Author)
Format: Book
Language:English
Published: Shelter Island, NY : Manning, ©2025
Subjects:
Related Items:Online version: Machine learning system design.
Classic Catalogue: View this record in Classic Catalogue
Table of Contents:
  • Part 1. Preparations. Essentials of machine learning system design
  • Is there a problem?
  • Preliminary research
  • Design document
  • Part 2. Early stage. Loss functions and metrics
  • Gathering datasets
  • Validation schemas
  • Baseline solution
  • Part 3. Intermediate steps. Error analysis
  • Training pipelines
  • Features and feature engineering
  • Measuring and reporting results
  • Part 4. Integration and growth. Integration
  • Monitoring and reliability
  • Serving and inference optimization
  • Ownership and maintenance.