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Update explanation in the "What is AliroEd?" #541

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Jan 16, 2023
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Update explanation in the "What is AliroEd?" #541

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Update explanation in the "What is AliroEd?"
HyunjunA Jan 16, 2023
49b774e
Merge branch 'EpistasisLab:master' into master
HyunjunA Jan 16, 2023
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35 changes: 23 additions & 12 deletions raspberrypi/intropage/index.html
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Expand Up @@ -198,15 +198,12 @@ <h1 class="fw-light text-white">What is AliroEd?</h1>
class="lead text-white"
style="padding-left: 50px; padding-right: 50px"
>
AliroEd is a software for users who are not familiar with machine
learning. Users can experience machine learning tasks on Raspberry
Pi 4 with AliroEd. Users can download the raspberry pi image from
the AliroEd website. Users can easily install and run AliroEd on
Raspberry Pi 4 using this image. AliroEd and the Raspberry Pi
image provided in this website, are developed by the AI Research
Center at the Computational Biomedicine Department Cedars-Sinai
Medical Center, Los Angeles, CA, USA. Please click the following
button for more information.
AliroEd is a software package running with Raspberry Pi 400 for
users who are new to machine learning and AI. Users can experience
machine learning tasks on Raspberry Pi 400 with AliroEd. Users can
download the AliroEd-RPI-image from the AliroEd website. Users can
easily install and run the AliroEd on Raspberry Pi 400 using this
image.
</p>
<p>
<!-- <a id='infanddownload' href="./infAndDownloadpage.html" class="btn btn-primary my-2">Download</a> -->
Expand All @@ -230,9 +227,23 @@ <h1 class="fw-light text-white">
class="lead text-white"
style="padding-left: 50px; padding-right: 50px"
>
If you are interested in getting intuitions about machine
learning, please click the below button in the card to see the
visual explanation of decision tree.
If you are interested in learning about machine learning
visualization, please click the below button in the card to see
the visual explanation of decision tree. In the visual
explanation, with the iris dataset, you can see what features are
and how decision tree classifies the data points as one of the
three classes (setosa, versicolor, virginica), based on the
features. The dataset can be found at
<a
style="color: #000000; font-weight: bold"
href="https://github.com/EpistasisLab/pmlb/tree/master/datasets"
>Penn Machine Learning Benchmarks</a
>. The source code is in
<a
href="https://github.com/EpistasisLab/Aliro"
style="color: #000000; font-weight: bold"
>the github repository.</a
>
</p>
<!-- <p>
<a id='loadingbutton' href="#" class="btn btn-primary my-2">Loading AliroEd ...</a>
Expand Down