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A comprehensive guide to the classification methodology in supervised learning, covering the complete ML workflow from data preparation to model evaluation, plus an in-depth look at Multinomial Naive Bayes for text classification.
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A comprehensive guide to the K-Nearest Neighbors (KNN) algorithm, covering theory, implementation, distance metrics, parameter tuning, and practical applications with real-world examples.- Published on
A comprehensive guide to decision trees in machine learning, covering theory, implementation, advantages, disadvantages, and practical applications with real-world examples.