A company deploys a recommendation model for its e-commerce site. After launch, the team wants to continuously improve the model based on how users interact with the recommendations. Which mechanism best supports this goal?

Freeze the model after deployment to ensure consistent recommendations.

Implement a feedback loop that logs user clicks and purchases on recommended items and periodically retrains the model with this new data.

Conduct a one-time user survey after launch and implement all suggested changes.

Monitor model accuracy on the original test set and only retrain if accuracy drops.

A data science team has built a dashboard for business analysts to explore model predictions. Which activity is an example of user testing?

Running a SQL query to check the dashboard's data source for missing values

Comparing the model's output to historical results to confirm accuracy

Measuring the dashboard's load time under peak concurrent usage

Observing analysts as they attempt to interpret the dashboard and complete a typical analysis task

What is the role of visualization in explaining model behavior?

To replace the need for model documentation

To increase the model's prediction speed

To make complex model insights accessible and understandable

To automatically tune hyperparameters

What does SHAP (SHapley Additive exPlanations) compute for a model prediction?

The optimal hyperparameters for the model

The contribution of each feature to the prediction

CertNexusCertified Data Science Practitioner (CDSP)

Domain 7Objective 1

Objective 7.1 Report Findings CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 6)

Part of the 7.0 Communication findings domain, which accounts for 4-7% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.

64questions here

13free pages

31concepts

4-7%of the exam

31 Concepts in This Objective

POC Web App Implementation
Web Frameworks (Flask, Django)
Basic HTML
CSS
Deriving Insights from Findings
Feature Importance Analysis
Model Results Presentation
Lift and Gain Charts
Model Transparency and Explainability
Intrinsic Explainable Methods
Post Hoc Explainable Methods
Visualization for Explanation
Attention Mechanisms
Avoiding Black-Box Techniques
XAI Frameworks and Tools
SHAP
LIME
ELI5
What-If Tool
AIX360
Skater
Model Lifecycle Documentation
ML Design and Workflow
Code Comments
Data Dictionary
Model Cards
Impact Assessments
Stakeholder Analysis
User Testing
Feedback Loops
Participatory Design

Questions 26–30

26application · medium
A company deploys a recommendation model for its e-commerce site. After launch, the team wants to continuously improve the model based on how users interact with the recommendations. Which mechanism best supports this goal?
Select an answer first
27foundation · easy
A data science team has built a dashboard for business analysts to explore model predictions. Which activity is an example of user testing?
Select an answer first
28foundation · easy
What is the role of visualization in explaining model behavior?
Select an answer first
29foundation · easy
What does SHAP (SHapley Additive exPlanations) compute for a model prediction?
Select an answer first
30foundation · easy
Which Python web framework is known for its simplicity and is often used to quickly create a small web interface for serving machine learning model predictions?
Select an answer first

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