Practice Step 5: Make Predictions (9.6) - Chapter 9: End-to-End Machine Learning Project – Predicting Student Exam Performance

Practice: Step 5: Make Predictions

Lesson 9.6End-to-End Machine Learning Project – Predicting Student Exam Performance

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9 questions

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6 sample questions

Question 1.
What method do we use to generate predictions from our Logistic Regression model?
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Think about functions associated with model output.
Question 2.
In the context of our dataset, what does a prediction of '1' represent?
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Consider how we labeled the outcomes.
3Question 3.
What does y_pred contain after making predictions?
- The training data
- Predictions of pass or fail
- Feature variables
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Remember what we discussed about output variables.
4Question 4.
Is Logistic Regression used for predicting multiple outcomes?
- True
- False
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Consider the nature of our dataset's target variable.
Question 5.
Given a new dataset of students with additional features like past grades and family background, how could you enhance predictions made by your model?
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Think about how more data might change results.
Question 6.
Discuss the potential ethical implications of using predictive models in education. What steps would you take to ensure fairness?
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Consider fairness and inclusivity in model training.

5 more questions in this section. Enroll free to practise them all.