Top Considerations for Building a Production-Ready AI/ML Environment
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Global data storage is expected to grow exponentially in the next 5 years. Mid- and large-sized organizations are beginning to understand that it’s not just about collecting this data, but using it to deliver business insights, automate tasks, and advance system capabilities.
To turn data into a critical business asset, organizations are adopting artificial intelligence (AI), machine learning (ML), and deep learning (DL). This e-book highlights top considerations for building a production-ready AI/ML environment to support business goals.
DOWNLOAD NOW and:
- See why containers and container orchestration are important for AI/ML
- Learn about the benefits of application management and DevOps for AI/ML
- Consider the importance of a hybrid cloud platform and data pipelines in an AI/ML initiative
- Discover the importance of building an open, flexible foundation for AI/ML
- Find the certified Kubernetes Operators you need for AI/ML on Red Hat Marketplace
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