From the course: Applied AI Auditing in Python
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Data auditing example - Python Tutorial
From the course: Applied AI Auditing in Python
Data auditing example
- [Instructor] In this video, I'll walk you through conducting a data audit. We're going to use the Boston Housing dataset to show how discrimination gets encoded in algorithms, in this case, three datasets influenced by social biases. We start here by loading our necessary libraries, and now, I'll load the dataset from sklearn. As you can actually see, we get a warning here. Because of the biases we'll cover in this video, the dataset has been removed as a default from sklearn, but we'll use it anyway to explore why there's controversy around it. I'd like to point out that this error message handles this issue really well. There's an alternate method for accessing the dataset for cases like this one where we're inspecting bias. There's also alternate datasets for those hoping to train models based on housing prices. It even includes links to papers covering the impact of the bias dataset for further learning. Let's dive in by loading the actual dataset using the alternate code given.…
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