3.3.Quiz_From Deployment to Feedback - sj50179/IBM-Data-Science-Professional-Certificate GitHub Wiki

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Question 1

The final stages of the data science methodology are an iterative cycle between Modelling, Evaluation, Deployment, and Feedback.

True

Correct

Question 2

Select the correct statement about the Feedback stage of the data science methodology.

Feedback is not required once launched.

Feedback is not helpful and gets in the way.

Feedback is essential to the long term viability of the model.

None of the above statements are correct.

Correct

Question 3

Deploying a model into production represents the end of the iterative process that includes Feedback, Model Refinement, and Redeployment.

False

Correct

Question 4

The data science methodology is a specific strategy that guides processes and activities relating to data science only for text analytics.

False.

Correct

Question 5

A data scientist determines that building a recommender system is the solution for a particular business problem at hand. What stage of the data science methodology does this represent?

Model Evaluation.

Modeling.

Deployment.

Analytic Approach.

Correct

Correct. The selection of a model to use should happen in the Analytic Approach stage.

Question 6

A data scientist, John, was asked to help reduce readmission rates at a local hospital. After some time, John provided a model that predicted which patients were more likely to be readmitted to the hospital and declared that his work was done. Which of the following best describes this scenario?

John still needed to collect more data.

John only provided one model as a solution and he should have provided multiple models.

John’s mistake is that he lied in the Analytic Approach step of the data science methodology.

Even though John only submitted one solution, it might be a good one. However, John needed feedback on his model from the hospital to confirm that his model was able to address the problem appropriately and sufficiently.

Correct

Question 7

What do data scientists typically use for exploratory analysis of data and to get acquainted with it?

They use descriptive statistics and data visualization techniques.

They begin with regression, classification, or clustering.

They use deep learning.

They use support vector machines and neural networks as feature extraction techniques.

Correct

Question 8

Data scientists may frequently return to a previous stage to make adjustments, as they learn more about the data and the modeling.

True.

Correct

Question 9

For predictive models, a test set, which is similar to – but independent of – the training set, is used to determine how well the model predicts outcomes. This is an example of what step in the methodology?

Data Requirements.

Deployment.

Analytic Approach.

Model Evaluation.

Correct

Question 10

What are three important reasons that data scientists should maintain continuous communication with business sponsors throughout a project?

• _ So that business sponsors can ensure the work remains on track to generate the intended solution._

Correct

Correct.

• Actually, data scientists do not need to maintain a continuous communication with business sponsors and stakeholders.

• So that business sponsors can review intermediate findings.

Correct

Correct.

• So that business sponsors can provide domain expertise.

Correct

Correct.