AI and Analytics in Production

How to Make It Work

by Ted Dunning and Ellen Friedman © 2018. Published by O'Reilly.

Value from big data becomes real when your data-intensive AI, machine learning and analytics applications go into production. That can be challenging, but this non-technical but practical guide helps by showing you what has made others successful.

Approaches such as Kubernetes for containerization, an effective data platform, streaming microservices and multi-tenancy can help you deploy across multi-cloud, hybrid cloud, and IoT edge computing. Whether you already have data-driven applications in production, are about to deploy, or are just getting started, you'll find something helpful in this book.

Download this book to:

  • Recognize goals, challenges, and potential pitfalls of deploying Ai and analytics applications to production
  • Learn how best to plan, design, and execute large data systems tied to practical business considerations
  • Develop a production-ready culture across your organization
  • Focus on the special case of machine learning and AI in production
  • Examine MapR, a data platform with the technical capabilities to support emerging trends for large-scale data
  • Explore a range of design patterns that work well for production customers in multiple industries

 

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