** Introduction to Classification in Machine Learning: A Step-by-Step Guide

Classification is a fundamental concept in machine learning, used to predict categories or labels. This step-by-step guide provides an introduction to classification, including its types (binary, multi-class, and multi-label), evaluation metrics, and popular algorithms.

The article covers essential topics such as features and labels, training and testing data, and hyperparameter tuning. It also includes code examples for installing necessary libraries, loading a sample dataset, and selecting a suitable algorithm.

A balanced approach is taken to present factual information without bias, providing relevant context and background information while avoiding speculation or sensationalism. The article's tone remains neutral, focusing on the broader implications of classification in machine learning rather than specific individuals or groups.

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Source: https://dev.to/ayas_tech_2b0560ee159e661/introduction-to-classification-in-machine-learning-3ge5