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* Create Person “timothy-utter/readme”

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* Create Blog “2023/09-26/digital-arts-and-humanities-project-development-at-idah/readme”

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Co-authored-by: ezengels <[email protected]>
Co-authored-by: Bruce W. Herr II <[email protected]>
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12 changes: 9 additions & 3 deletions content/macroscope/19/4/readme.md
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en:
sequence: 4
body: >-
You’ve probably heard of “machine learning,” but maybe you’re a little fuzzy on how it works. Not to worry—here’s a friendly introduction to machine learning that will give you the basics and beyond. It begins with a problem: How does a machine “learn” to tell one thing from another? From there, this scrollytelling tutorial takes us through the process in a way that is both informative and easy to follow. Machine learning algorithms are powerful tools in the field of artificial intelligence. This macroscope is a great first step in understanding how to put that power to use.
Today’s digital atlases pull together massive amounts (insert units) of data
in order to present a comprehensive view of a topic. Given this volume of
data, machine learning techniques are critical for analyzing or identifying
patterns in the underlying data. This macroscope demonstrates key machine
learning approaches using a dataset about houses, with a goal of identifying
whether houses are located in New York City or San Francisco. Brush up on
data dimensions, finding boundaries, and decision trees by scrolling through
*A Visual Introduction to Machine Learning*.
Explore the interactive online at [http://www.r2d3.us/visual-intro-to-machine-learning-part-1](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/).
externalLink: http://www.r2d3.us/visual-intro-to-machine-learning-part-1
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- tony-chu/readme
title: A visual introduction to machine learning
image:
sm: ml_kioskv2-2.png
sm: viml4.png
med: ml_large.png
lg: ml_large.png
year: 2015
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