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index.html
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<!DOCTYPE html>
<html lang="" xml:lang="" xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8"/>
<meta content="pandoc" name="generator"/>
<meta content="width=device-width, initial-scale=1.0, user-scalable=yes" name="viewport"/>
<title>
Zwergon’s Homepage.
</title>
<link href="./static/pandoc.css" rel="stylesheet"/>
<!-- Our JS -->
<script src="static/pypi_checker.js" type="text/javascript">
</script>
</head>
<body>
<header id="title-block-header">
<h1 class="title">
Zwergon’s Github Homepage.
</h1>
</header>
<h2 id="a-few-dataset-to-download">
Few datasets to download
</h2>
<ul>
<li>
<a href="./datasets/wb_dataset.tar.gz">
"Wind Bench Dataset
</a>
for testing
<a href="https://github.com/zwergon/wind_bench">
wb-virtual
</a>
</li>
</ul>
<h2 class="text-header">
Few packages to install
</h2>
<p>
These are package hosted on github that you may install if you want.
<br/>
You can install packages with :
<pre><code>pip install <package_name> --extra-index-url https://zwergon.github.io/</code></pre>
</p>
<h3 class="text-header">
List of packages
</h3>
<a class="card" href="rocknet/">
rocknet
<span>
</span>
<span class="version">
0.0.1
</span>
<br/>
<span class="description">
This project aims at learning using pytorch a classifier able to predict Rock type given a picture of it.
</span>
</a>
<a class="card" href="mdataset/">
mdataset
<span>
</span>
<span class="version">
2.0.4
</span>
<br/>
<span class="description">
Management of PostgreSQL database for RockNet and MetNet project. Versionnig of dataset. Create a Python package that takes VisionDataset standards to access RockNet and MetNet databaes
</span>
</a>
<a class="card" href="iapytoo/">
iapytoo
<span>
</span>
<span class="version">
0.0.2
</span>
<br/>
<span class="description">
a public-github-hosted repo that defines a lightweight pytorch toolkit to quickly build one simple AI
learning/predict/deploy process tracked by mlflow framework.
</span>
</a>
<a class="card" href="wb-virtual/">
wb-virtual
<span>
</span>
<span class="version">
0.0.2
</span>
<br/>
<span class="description">
A private github-hosted repo that illustrates how to perform
virtual sensing on a bench dataset provided by the DTU.
</span>
</a>
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var content = lnk.textContent.trim().replace(/\s\s+/g, ' ').split(" ");
var pkg_name = content[0];
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function mark_red() {
lnk.classList.add("redalert");
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</body>
</html>