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5 Lessons

Classification Algorithms

Focus on this chapter's key concepts. Dive into each topic for a detailed understanding with examples and structured notes.

K-Nearest Neighbors (KNN) algorithm and distance metrics

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1 of 5 Lessons

Decision Trees (Entropy, Gini impurity, Information Gain)

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2 of 5 Lessons

Random Forest and Bagging concepts

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3 of 5 Lessons

Support Vector Machines (SVM) and Margin maximization

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4 of 5 Lessons

Naive Bayes classifier and Bayes' theorem application

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5 of 5 Lessons

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Linear and Logistic Regression

Model Evaluation Metrics