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Python Deep Learning - Second Edition
book

Python Deep Learning - Second Edition

by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
January 2019
Intermediate to advanced content levelIntermediate to advanced
386 pages
11h 13m
English
Packt Publishing
Content preview from Python Deep Learning - Second Edition

Linear and logistic regression

Regression algorithms are a type of supervised algorithm that uses features of the input data to predict a value, such as the cost of a house, given certain features, such as size, age, number of bathrooms, number of floors, and location. Regression analysis tries to find the value of the parameters for the function that best fits an input dataset.

In a linear-regression algorithm, the goal is to minimize a cost function by finding appropriate parameters for the function, over the input data that best approximates the target values. A cost function is a function of the error, that is, how far we are from getting a correct result. A popular cost function is the mean square error (MSE), where we take the square ...

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Publisher Resources

ISBN: 9781789348460Supplemental Content