Ted Dunning
Author
Publisher
O'Reilly Media, Inc
Pub. Date
2021
Language
English
Description
Getting large-scale data-driven applications for AI and analytics into production doesn't have to be challenging. Technical managers, senior technologists, and implementers today often overlook fundamental aspects of design and data infrastructure--aspects that can make the difference between failed approaches and reliable, successful production systems. In this exclusive report, you'll learn which practices work--and which don't--at large and innovative...
Author
Publisher
O'Reilly Media
Pub. Date
[2018]
Language
English
Description
If you've begun to deploy large-scale data systems into production, or have at least explored the process, this practical ebook shows business team leaders, business analysts, and technical developers how to make your big data analytics, machine learning, and AI initiatives production ready. Authors Ted Dunning and Ellen Friedman provide a non-technical guide to best practices for a process that can be quite challenging. Rather than provide a complex...
Author
Publisher
O'Reilly Media
Pub. Date
2017.
Language
English
Description
Many organizations have begun to rethink the strategy of allowing regional teams to maintain independent databases that are periodically consolidated with the head office. As businesses extend their reach globally, these hierarchical approaches no longer work. Instead, an enterprise's entire data infrastructure--including multiple types of data persistence--needs to be shared and updated everywhere at the same time with fine-grained control over who...
Author
Publisher
O'Reilly Media
Pub. Date
[2017]
Language
English
Description
To succeed with machine learning or deep learning, you must handle the logistics well. Simply put, you need an effective management system for overall data flow and the evaluation and deployment of multiple models as they move from prototype to production. Without that, your project will most likely fail. This report examines what you need for effective data and model management in real-world settings, including globally distributed cloud or on-premises...
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