An Introduction to Redis-ML (Part 6) - DZone AI

In previous posts, we learned how to use and scikit-learn to build a real-time classification and regression engine, how to use linear regression to predict housing prices, and how to use decision trees to predict survival rates. We even took a small detour into R to demonstrate ML toolkit independence, but one question we haven't focused on is, Why? Why would we want to use Redis for a real-time predictive engine? If we look at the landscape of machine learning toolkits, most focus on the learning side of ML, leaving the problem of a predictive engine to the reader. This is where Redis fills a gap; instead of trying to build a custom server, developers can rely on a familiar, full-featured data store to build their applications.