This post provides an introduction to classification models in machine learning. It covers the concept of feature selection, the math behind classification, evaluation metrics for classification models, and different types of classification models. The post emphasizes the importance of training and generalization in building robust classification systems.
Table of contents
Foundations of ClassificationFeature SelectionThe Math Behind ClassificationEvaluation MetricsTypes of Classification ModelsTraining and GeneralizationReal-world Applications of Classification ModelsConclusionReferencesIn Plain English 🚀32 Impressions