Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
by Valliappa Lakshmanan, Sara Robinson, Michael Munn
A practical guide offering reusable design patterns to overcome common challenges in data preparation, model building, and MLOps for machine learning systems.
About This Book
This book presents reusable design patterns that address recurring issues in machine learning workflows.
Readers will find guidance on data preparation, model building, and operationalizing ML systems.
The patterns help teams improve reliability, scalability, and maintainability of their machine learning projects.
Content focuses on practical solutions drawn from real-world engineering experience.
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