You're reading from Machine Learning with Go Quick Start Guide

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Published inMay 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781838550356

Edition1st Edition

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Machine Learning

Authors (2):

Michael Bironneau

Toby Coleman

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Example – exploring body mass index data with gonum/plot

In the previous section, we introduced gophernotes and Gota. In this section, we will explore a dataset containing 500 samples of gender, height, and BMI index. We will do this using the gonum/plot library. This library, which was originally a fork of the 2012 Plotinum library^[15], contains several packages that make creating data visualizations in Go much easier^[16]:

The plot package contains a layout and formatting interface.
The plotter package abstracts the layout and formatting for common plot types, such as bar charts, scatter plots, and so on.
The plotutil package contains utility funcs for common plot types.
The vg package exposes an API for vector graphics and is particularly useful when exporting plots to other software. We will not be covering this package.

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Machine Learning with Go Quick Start Guide

Published in: May 2019Publisher: PacktISBN-13: 9781838550356

Authors (2)

Michael Bironneau

Michael Bironneau is an award-winning mathematician and experienced software engineer. He holds a PhD in mathematics from Loughborough University and has worked in several data science and software development roles. He is currently technical director of the energy AI technology company, Open Energi.
Read more about Michael Bironneau

Toby Coleman

Toby Coleman is an experienced data science and machine learning practitioner. Following degrees from Cambridge University and Imperial College London, he has worked on the application of data science techniques in the banking and energy sectors. Recently, he held the position of innovation director at cleantech SME Open Energi, and currently provides machine learning consultancy to start-up businesses.
Read more about Toby Coleman

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