Part 1. Classification

The first two parts of this book are on supervised learning. Supervised learning asks the machine to learn from our data when we specify a target variable. This reduces the machine’s task to only divining some pattern from the input data to get the target variable.

We address two cases of the target variable. The first case occurs when the target variable can take only nominal values: true or false; reptile, fish, mammal, amphibian, plant, fungi. The second case of classification occurs when the target variable can take an infinite number of numeric values, such as 0.100, 42.001, 1000.743,.... This case is called regression. We’ll study regression in part 2 of this book. The first part of this book focuses on classification. ...

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