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Course# CS-439: Optimization for machine learning

Summary

This course teaches an overview of modern optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be discussed in theory and in implementation.

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Instructors (2)

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Related concepts (42)

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternative

Gradient method

In optimization, a gradient method is an algorithm to solve problems of the form
:\min_{x\in\mathbb R^n}; f(x)
with the search directions defined by the gradient of the function at th

Upper and lower bounds

In mathematics, particularly in order theory, an upper bound or majorant of a subset S of some preordered set (K, ≤) is an element of K that is greater

Accuracy and precision

Accuracy and precision are two measures of observational error.
Accuracy is how close a given set of measurements (observations or readings) are to their true value, while precision is how close the

Time

Time is the continued sequence of existence and events that occurs in an apparently irreversible succession from the past, through the present, into the future. It is a component

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