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An introduction to fundamental principles of probability and statistics, covering key concepts such as random variables, probability distributions, expectation, variance, and common statistical measures.

KNN is a simple yet powerful algorithm used for classification and regression tasks in machine learning. This article provides an overview of the KNN algorithm, its working principles, and practical applications.

This article introduces the common notations used in machine learning, including vectors, matrices, datasets, and functions.

Linear regression is a fundamental algorithm in machine learning used for predicting continuous outcomes. This article provides an in-depth understanding of linear regression, including its mathematical formulation, assumptions, and practical applications.

An introduction to basic concepts in linear algebra and calculus, including vectors, matrices, derivatives, and integrals.