How to Deliver Faster, More Reliable Prediction Engines with Less Custom Development
Date: Wednesday, August 15, 2018 at 11am PDT / 2pm EDT
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.
In this webcast you will learn how to:
- Apply Redis to solving machine learning problems
- Build a real-time housing price predictor with Redis
- Use Redis to scale the evaluation of decision trees
- Deploy standard machine learning statistical models in Redis