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MLOpsdevops~10 mins

Evidently AI for monitoring in MLOps - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to import Evidently's Report class.

MLOps
from evidently.report import [1]
Drag options to blanks, or click blank then click option'
ADashboard
BReport
CMonitor
DAnalyzer
Attempts:
3 left
💡 Hint
Common Mistakes
Importing a non-existent class like Dashboard or Monitor.
2fill in blank
medium

Complete the code to add a data drift metric to the Evidently report.

MLOps
from evidently.metric_preset import [1]

report = Report(metrics=[DataDriftPreset()])
Drag options to blanks, or click blank then click option'
ADataDriftPreset
BClassificationPreset
CDataQualityPreset
DRegressionPreset
Attempts:
3 left
💡 Hint
Common Mistakes
Using presets for quality or model performance instead of data drift.
3fill in blank
hard

Fix the error in the code to run the Evidently report on current and reference data.

MLOps
report.run(current_data=[1], reference_data=ref_data)
Drag options to blanks, or click blank then click option'
Acurrent_df
Bcurrent_data
Cdata_current
Dref_data
Attempts:
3 left
💡 Hint
Common Mistakes
Passing the reference data variable as current data.
4fill in blank
hard

Fill both blanks to save the Evidently report as an HTML file.

MLOps
with open([1], [2]) as f:
    f.write(report.as_html())
Drag options to blanks, or click blank then click option'
A'report.html'
B'w'
C'r'
D'report.json'
Attempts:
3 left
💡 Hint
Common Mistakes
Using read mode 'r' or wrong file extensions like .json.
5fill in blank
hard

Fill all three blanks to create a monitoring dashboard with Evidently and save it as HTML.

MLOps
from evidently.dashboard import [1]
from evidently.dashboard.tabs import [2]

dashboard = Dashboard(tabs=[[3]()])
Drag options to blanks, or click blank then click option'
ADashboard
BDataDriftTab
DReport
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing Report with Dashboard or using wrong tab names.