Abstract
Machine learning, a rapidly growing subfield of computer science, has had a
significant impact on many industries and our lives. This chapter discusses the brief history of
machine learning, its widespread adoption as a de facto feature, and fundamental concepts such
as supervised and unsupervised learning, regression and classification, and underfitting and
overfitting. We also emphasize the importance of understanding machine learning through
numerical examples, which can bridge the gap between abstract mathematical theories and
practical applications of machine learning algorithms. By developing a strong foundation in
machine learning, readers/students can harness its potential to address challenges and
opportunities across diverse sectors.
Keywords: Numerical Examples, Machine Learning History, Supervised Learning, Unsupervised Learning, Regression, Classification, Underfitting, Overfitting
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