Quiz – Frame The Problem

Question 1 of 6

1. Question

Fixed hardware requirements

Machine learning tasks with defined variables

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Random experiments without goals

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Marketing slogans

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Fixed hardware requirements

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Question 2 of 6

2. Question

Avoiding all stakeholder input

Classifying problem types and setting explicit success metrics

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Ignoring metrics until launch

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Choosing the largest model available

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Avoiding all stakeholder input

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Question 3 of 6

3. Question

Writing any documentation

Algorithmic bias in responsible deployment

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Faster training times

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The need for any data

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Writing any documentation

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Question 4 of 6

4. Question

To skip model selection

They connect the business objective to the ML task

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To increase token cost

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To replace the success metric

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To skip model selection

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Question 5 of 6

5. Question

Match each framing activity to its purpose.

Sort elements

Clarify the business objective
Select data relevant to the task
Pick a suitable ML approach
Measure alignment with business needs

Define the challenge

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Identify variables

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Classify problem type

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Set success metrics

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Question 6 of 6

6. Question

Fill in the blanks.

Problem framing translates business Fill in the blank 1 of 3 into machine learning Fill in the blank 2 of 3 and sets explicit success Fill in the blank 3 of 3 .