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Designing Machine Learning Systems

Author: Chip Huyen
Binding: Paperback
Paper Quality: Black White Paper
Category: Computer Science / Machine Learning / Systems Design
Recommended For: Software engineers, data scientists, ML researchers, and students building production-ready machine learning systems.

Key points:

1. Comprehensive guide to designing machine learning systems for production.
2. Emphasis on an iterative approach for continuous refinement.
3. Covers fundamental principles, common pitfalls, and best practices.
4. Practical insights from industry expert Chip Huyen.
5. Integration of agile methodologies and deployment techniques.
6. Real-world case studies and examples for practical understanding.
This book will help you tackle scenarios such as:

  • Engineering data and choosing the right metrics to solve a business problem
  • Automating the process for continually developing, evaluating, deploying, and updating models
  • Developing a monitoring system to quickly detect and address issues your models might encounter in production
  • Architecting an ML platform that serves across use cases
  • Developing responsible ML systems

                                                       ════ ⋆★⋆ ═══

 Writer                 ✤      Chip Huyen (Author)

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