Introducing MLOps: How to Scale Machine Learning in the Enterprise

This book is a game-changer for data scientists and application engineers who want to operationalize their machine learning models and drive real business impact.

With MLOps, you can reduce friction throughout ML pipelines and workflows, refine models through retraining and periodic tuning, and ensure long-term accuracy.

The book provides insights into the five steps of the model life cycle - Build, Preproduction, Deployment, Monitoring, and Governance - and shows how to design MLOps processes that minimize organizational risks with unbiased, fair, and explainable models.

Whether you're deploying ML models for pipeline deployment or external business systems, this book has got you covered.

Don't miss out on the opportunity to fulfill your data science value and revolutionize your organization's approach to machine learning.