### Higher-Order Derivatives

Higher-order derivatives can capture information about a function that first-order derivatives on their own cannot capture. First-order derivatives can capture important information, such as the

July 30, 2021
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Higher-order derivatives can capture information about a function that first-order derivatives on their own cannot capture. First-order derivatives can capture important information, such as the

July 28, 2021
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Gradient descent procedure is a method that holds paramount importance in machine learning. It is often used for minimizing error functions in classification and regression

July 26, 2021
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Partial derivatives and gradient vectors are used very often in machine learning algorithms for finding the minimum or maximum of a function. Gradient vectors are

July 23, 2021
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Vector valued functions are often encountered in machine learning, computer graphics and computer vision algorithms. They are particularly useful for defining the parametric equations of

July 21, 2021
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Integral calculus was one of the greatest discoveries of Newton and Leibniz. Their work independently led to the proof, and recognition of the importance of

July 19, 2021
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It is often desirable to study functions that depend on many variables. Multivariate calculus provides us with the tools to do so by extending the

July 15, 2021
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The derivative defines the rate at which one variable changes with respect to another. It is an important concept that comes in extremely useful in

July 14, 2021
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Many areas of calculus require an understanding of continuous functions. The characteristics of continuous functions, and the study of points of discontinuity are of great

June 22, 2021
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We have previously seen that calculus is one of the core mathematical concepts in machine learning that permits us to understand the internal workings of

June 21, 2021
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Calculus is one of the core mathematical concepts in machine learning that permits us to understand the internal workings of different machine learning algorithms. One

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