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Machine Learning with Go Quick Start Guide

You're reading from   Machine Learning with Go Quick Start Guide Hands-on techniques for building supervised and unsupervised machine learning workflows

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781838550356
Length 168 pages
Edition 1st Edition
Languages
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Authors (2):
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Michael Bironneau Michael Bironneau
Author Profile Icon Michael Bironneau
Michael Bironneau
Toby Coleman Toby Coleman
Author Profile Icon Toby Coleman
Toby Coleman
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Toc

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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