| FazBrowse GitHub Viewer | Trending | | Home |
| Tools: [Download Repo ZIP] [Original HTTPS Page] |
| Name | Name | Last commit date | ||
|---|---|---|---|---|
In many applications, trust in an AI system will come from its ability to ‘explain itself.’ But when it comes to understanding and explaining the inner workings of an algorithm, one size does not fit all. Different stakeholders require explanations for different purposes and objectives, and explanations must be tailored to their needs. While a regulator will aim to understand the system as a whole and probe into its logic, consumers affected by a specific decision will be interested only in factors impacting their case – for example, in a loan processing application, they will expect an explanation for why the request was denied and want to understand what changes could lead to approval.
AI Explainability 360 (AIX360) is an open source toolkit that includes algorithms that span the different dimensions of ways of explaining along with proxy explainability metrics.
In this workshop you will explore different kinds of explanations suited to different users. You will learn:
Jupyter notebooks are an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.
In this workshop we will use IBM Watson Studio to run a notebook. For this you will need an IBM Cloud account. The following steps will show you how sign up and get started. When you have the notebook up and running we will go through the notebook.
When you have used Watson Studio before, you can skip the next few steps. Go straight to the Resources list and click on Watson Studio and then click on Get Started. This will open a new Tab with Cloud Pak For Data that includes Watson Studio.
When you have just created an account, click Create Resource at the top of the Resources page. You can find the resources under the hamburger menu at the top left:
You are now ready to follow along with the workshop in the notebook!
Optional local install on Mac:
Install Anaconda
Open terminal and create a new environment:
> conda create --name aix360 python=3.7
> conda activate aix360
Just in case: > conda env remove --name aix360
Add kernel to Jupyter notebooks:
> python -m ipykernel install --user --name aix360 --display-name "Python37 (aix360)"
Start notebooks: > jupyter notebook
| Back | FazBrowse Home | New Git URL |