The primary focus of most machine learning research and development centers on the training side of the problem. Multiple frameworks, in every language, provide developers with access to a host of data manipulation and training algorithms, but until recently developers had virtually no frameworks for building predictive engines from trained ML models. Most developers resort to building custom applications, yet building highly available and performant applications is difficult. Redis in conjunction with the Redis-ML module provides a framework for developers to build predictive engines with familiar, off-the-shelf components. Developers can take advantage of all the features of Redis to deliver faster and more reliable prediction engines with less custom development.
|When:||July 17, 2018 | 10:00 am|
|Featured Speaker:||Tague Griffith, Head of Developer Advocacy, Redis.|
|Audience:||Redis and NoSQL Users|
Tague focuses on developer education, community growth, and support for the Redis community. Prior to joining Redis, he worked in infrastructure engineering building several high performant Redis Systems. He holds degrees in Computer Science from Stanford University.
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