Introducing MLOps: How to Scale Machine Learning in the Enterprise
(By Mark Treveil)
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| Author | Mark Treveil |
This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout.
This book helps you:
Fulfill data science value by reducing friction throughout ML pipelines and workflows
Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy
Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable
Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized”
