Evidently Cloud Quickstart
ML Monitoring “Hello world.” From data to dashboard in a couple of minutes.
1. Create an account
If not already, sign up for an Evidently Cloud account.
2. Get an access token
Click your username, select "personal token," generate and save the token.
3. Install the Python library
Install the Evidently Python library. You can this example in Colab or other Python environment.
Import the components to work with the dataset and send the metrics.
4. Create a new Project
Connect to Evidently Cloud using your access token and create a Project.
5. Collect metrics
Import the demo "adult" dataset as a pandas DataFrame.
Run a Data Quality Report and upload it to the Project.
We call each such evaluation a snapshot
.
7. View the Report
Visit Evidently Cloud, open your Project, and navigate to the "Report" tab to see the data stats.
8. Add a monitoring panel
Go to the "Dashboard" tab and enter the "Edit" mode. Add a new tab, and select the "Data quality" template.
You'll see a set of panels with a single data point. As you send more snapshots, you can track trends and set up alerts. You can choose from 100+ metrics and tests and add yours.
Want to see more?
Check out a more in-depth tutorial to learn the key workflows and architecture:
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