Practice Step 8: Predict for New Student - 9.9 | Chapter 9: End-to-End Machine Learning Project – Predicting Student Exam Performance | Machine Learning Basics
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Step 8: Predict for New Student

9.9 - Step 8: Predict for New Student

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What structure do we use for input when predicting a new student's outcome?

💡 Hint: Think about how we organize data in rows and columns.

Question 2 Easy

What is the output of the model's prediction?

💡 Hint: Recall the meaning of the numbers we used for passing and failing.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the output of the model.predict() function?

A numerical score
A binary outcome (pass/fail)
Descriptive statistics

💡 Hint: Think about how we defined passing and failing.

Question 2

True or False: You can feed non-numerical data directly into the predict function.

True
False

💡 Hint: What was the key preprocessing step in our project?

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You receive a new student's information indicating they studied for 3 hours, had 75% attendance but did not take a preparation course. Formulate a way to predict their outcome using the model. What will be your input, and what do you expect if their model performance is reliable?

💡 Hint: Compare their attributes against the previously successful students.

Challenge 2 Hard

If two students have identical attendance and preparation course status but different study hours (one studied 2 hours and another 10), how would you expect their predictions to differ? Use their study hours as a core factor in your prediction.

💡 Hint: Think back to how study hours affected past predictions.

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