Book description
More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Instead, many of these ML models do nothing more than provide static insights in a slideshow. If they aren’t truly operational, these models can’t possibly do what you’ve trained them to do.
This report introduces practical concepts to help data scientists and application engineers operationalize ML models to drive real business change. Through lessons based on numerous projects around the world, six experts in data analytics provide an applied four-step approach—Build, Manage, Deploy and Integrate, and Monitor—for creating ML-infused applications within your organization.
You’ll learn how to:
- Fulfill data science value by reducing friction throughout ML pipelines and workflows
- Constantly refine ML models through retraining, periodic tuning, and even complete remodeling to ensure long-term accuracy
- Design the ML Ops lifecycle to ensure that people-facing models are unbiased, fair, and explainable
- Operationalize ML models not only for pipeline deployment but also for external business systems that are more complex and less standardized
- Put the four-step Build, Manage, Deploy and Integrate, and Monitor approach into action
Table of contents
-
ML Ops: Operationalizing Data Science
- An Introduction to ML Ops and Operationalizing Data Science Models
- Introducing the Four-Step ML Ops Approach
- Build
- Manage
- Deploy and Integrate
- Monitor
- Case Study: Operationalizing Data Science in the Manufacturing Industry—Digital Twin Models
- Case Study: Operationalizing Data Science in the Insurance Industry—Dynamic Pricing Models
- Conclusion
Product information
- Title: ML Ops: Operationalizing Data Science
- Author(s):
- Release date: April 2020
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492074656
You might also like
book
How to Lead in Data Science
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal …
video
Machine Learning Algorithms in 7 Days
Are you really keen to learn some cool machine learning algorithms that are making headlines these …
video
Machine Learning with Python for Everyone, Part 3: Fundamental Toolbox
4+ Hours of Video Instruction Code-along sessions move you through the development of classification and regression …
book
Personal Finance with Python: Using pandas, Requests, and Recurrent
Deal with data, build up financial formulas in code from scratch, and evaluate and think about …