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3 changes: 1 addition & 2 deletions README.md
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Expand Up @@ -16,8 +16,7 @@ use the FairNow API's. The recommended order is:

1. `Getting Started` - demonstrates how to configure authorization and make a first API call.
2. `Applications API` - create and read an `AI Application` with the API. `AI Applications` are a core building block for the FairNow system.
3. `Generating Synthetic User Bias Test Data` - construct a synthetic test data file to be used to simulate ML model bias evaluation. Constructing synthetic data is optonal.
4. `User Data Testing` - how to perform ML model bias testing via the API.
3. `Export Reports` - generate tsvs for application and company compliance, inventory, and risk and severity


### Note to contributors:
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2 changes: 1 addition & 1 deletion notebooks/Applications API.ipynb
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Expand Up @@ -114,7 +114,7 @@
"id": "8",
"metadata": {},
"source": [
"#### Save the `application_id` so that you can perform other compliance tasks for the application like approving it for deployment, testing for biases or adding evidence that a control has been met."
"#### Save the `application_id` so that you can perform other compliance tasks for the application like approving it for deployment or adding evidence that a control has been met."
]
},
{
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141 changes: 0 additions & 141 deletions notebooks/Generating Synthetic User Bias Test Data.ipynb

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