January 2025
Intermediate to advanced
614 pages
15h 37m
English
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4.1 Linear and Polynomial Regression
Linear regression is the simplest and most fundamental form of regression analysis in machine learning. This technique models the relationship between one or more input features (independent variables) and a continuous target variable (dependent variable) by fitting a straight line through the data points. The primary goal of linear regression is to find the best-fitting line that minimizes the overall prediction error.
In its simplest form, linear regression assumes a linear relationship between the input and output variables. This means that changes in the input variables result in proportional changes in the output variable. The model learns from labeled training data to determine the optimal parameters ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.