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Machine Learning for Developers

You're reading from  Machine Learning for Developers

Product type Book
Published in Oct 2017
Publisher Packt
ISBN-13 9781786469878
Pages 270 pages
Edition 1st Edition
Languages
Authors (2):
Rodolfo Bonnin Rodolfo Bonnin
Profile icon Rodolfo Bonnin
Md Mahmudul Hasan Md Mahmudul Hasan
View More author details

Table of Contents (10) Chapters

Preface Introduction - Machine Learning and Statistical Science The Learning Process Clustering Linear and Logistic Regression Neural Networks Convolutional Neural Networks Recurrent Neural Networks Recent Models and Developments Software Installation and Configuration

Regression analysis

This chapter will begin with an explanation of the general principles. So, let's ask the fundamental question: what's regression?

Before all considerations, regression is basically a statistical process. As we saw in the introductory section, regression will involve a set of data that has some particular probability distribution. In summary, we have a population of data that we need to characterize.

And what elements are we looking for in particular, in the case of regression? We want to determine the relationship between an independent variable and a dependent variable that optimally adjusts to the provided data. When we find such a function between the described variables, it will be called the regression function.

There are a large number of function types available to help us model our current data, the most common example being the linear, polynomial...

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