Abstract
This chapter delves into logistic regression, a widely used machine learning
algorithm for classification tasks, with a focus on maintaining accessibility by minimizing
abstract mathematical concepts. We present a concrete numerical example employing a small
dataset to predict the ease of selling houses in the property market, guiding readers through
each step of the process. Additionally, we supply sample codes and draw comparisons with the
logistic regression model available in the scikit-learn library. Upon completion of this chapter,
readers will have gained a comprehensive understanding of the inner workings of logistic
regression, its relationship to algorithm implementation and performance, and the knowledge
necessary to apply it to practical applications.