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<!DOCTYPE html>
<html lang="en">
<head>
<!-- Basic Page Needs
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<meta charset="utf-8">
<title>Machine Learning for Data Science (ML4DS) Winter Semester 2021/2022 @FUB</title>
<meta name="description" content="">
<meta name="author" content="">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<!--<link href="//fonts.googleapis.com/css?family=Raleway:400,300,600" rel="stylesheet" type="text/css">-->
<!-- CSS
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<link rel="stylesheet" href="css/normalize.css">
<link rel="stylesheet" href="css/skeleton.css">
<link rel="stylesheet" href="css/styles.css">
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<!--<link rel="icon" type="image/png" href="images/favicon.png">-->
</head>
<body>
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<div class="container">
<section class="header">
<div>
<!-- <img class="logo" src="fairdata-survey.png" width="200"/> -->
<h1 class="title">A survey on datasets for fairness-aware machine learning</h1>
</div>
</section>
<section class="summary">
<p>
The course provides an overview of machine learning methods and algorithms for different learning tasks, namely supervised, unsupervised and reinforcement learning.
In the first part of the course, for each task the main algorithms and techniques will be covered including experimentation and evaluation aspects.
In the second part of the course, we will focus on specific learning challenges including high-dimensionality, non-stationarity, label-scarcity and class-imbalance.
By the end of the course, you will have learned how to build machine learning models for different problems, how to properly evaluate their performance and how to tackle specific learning challenges.
</p>
</section>
<!-- <p class="alert" style="text-align:left;">
Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang and Eirini Ntoutsi “A survey on datasetsfor fairness-aware machine learning”. 2022. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. Wiley Periodicals, Inc. https://doi.org/10.1002/widm.1452
</p>
-->
<section class="code-links">
<a href="https://github.com/tailequy/fairness_dataset" class="button">
Code
</a>
<a href="https://doi.org/10.1002/widm.1452" class="button">
Paper
</a>
</section>
<section class="footer">
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</section>
</div>
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</body>
</html>