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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

Running Go interactively with gophernotes

Project Jupyter is a not-for-profit organization that was created to develop language-agnostic interactive computing for data science[3]. The result is a mature, well-supported environment to explore, visualize, and process data that can significantly accelerate development by providing immediate feedback and integrations with plotting libraries such as gonum/plot.

While its first iteration, called iPython, only supported Python-based handlers (called kernels) at first, the latest version of Jupyter has over 50 kernels that support dozens of languages, including three kernels for the Go language[4]. GitHub has support for rendering Jupyter files (called notebooks)[5], and there are various specialized hubs for sharing notebooks online, including Google Research Colabs[6], Jupyter's community hub called NBViewer[7], and its enterprise...

You have been reading a chapter from
Machine Learning with Go Quick Start Guide
Published in: May 2019
Publisher: Packt
ISBN-13: 9781838550356
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