Linear regression models the relationship between input variables and a continuous outcome using a linear equation. Understanding the concept helps practitioners choose training methods, evaluate model quality, and reduce errors when predictions are used in production systems. It also gives teams a clearer basis for comparing implementation options and deciding where the concept fits in a production system.
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