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Articles / Artificial Intelligence / Machine Learning
Posted 10 Jan 2019

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Tools to Help Optimize Deep-Learning Performance

10 Jan 2019CPOL
This article explores how developers can make deep-learning applications faster and more efficient by taking advantage of tools that optimize deep-learning code.

This article is in the Product Showcase section for our sponsors at CodeProject. These articles are intended to provide you with information on products and services that we consider useful and of value to developers.

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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About the Author

Chris_Riley
United States United States
ABOUT

Chris Riley is a technologist who has spent 12 years helping organizations transition from traditional development practices to a modern set of culture, processes and tooling. In addition to being a Gigaom Research analyst, he is an O’Reilly author, regular speaker, and subject matter expert in the areas of DevOps Strategy and culture and Enterprise Content Management. Chris believes the biggest challenges faced in the tech market is not tools, but rather people and planning.

Throughout Chris’s career he has crossed the roles of marketing, product management, and engineering to gain a unique perspective of how the deeply technical is used to solve real-world problems. By working with both early adopters and late, he has watched technologies mature from rough solutions to essential and transparent. In addition to spending his time understanding the market he helps ISVs selling B2D and practitioner of DevOps Strategy. He is interested in machine-learning, and the intersection of BigData and Information Management.

EXPERTISE

application lifecycle management (alm) devops enterprise content management (ecm) information architecture (ia) information governance

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