Making Real-Time Predictive Decisions with Redis-ML
|When:||July 17, 2018 | 9:00AM PST|
|Featured Speaker:||Tague Griffith, Head of Developer Advocacy, Redis Labs.|
|Audience:||Redis or/and NoSQL Users|
You Will Learn
- How to apply Redis to solving machine learning problems
- How to build a real-time housing price predictor with Redis
- How to use Redis to scale the evaluation of decision trees
- How to deploy standard machine learning statistical models in Redis
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.
Tague Griffith, Head of Developer Advocacy, Redis Labs
Tague focuses on developer education, community growth, and support for the Redis community. Prior to joining Redis Labs, he worked in infrastructure engineering building several high performant Redis Systems. He holds degrees in Computer Science from Stanford University.