An Introduction to Redis-ML (Part Two)

This post discusses linear regression and its implementation using Redis-ML module. It revisits the housing price predictor example from a previous post, but uses R instead of Python to perform the linear regression. The code demonstrates how different toolkits can be used in conjunction with Redis, emphasizing that the model is more important than the toolkit when using Redis for serving models. Additionally, it explains multiple linear regression and how to set up a key in Redis to store the represented multiple linear regression. The next post will cover logistic regression and building a classification engine with Redis.

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