Practice Step 4: Build the Model – Logistic Regression - 9.5 | Chapter 9: End-to-End Machine Learning Project – Predicting Student Exam Performance | Machine Learning Basics
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Step 4: Build the Model – Logistic Regression

9.5 - Step 4: Build the Model – Logistic Regression

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is logistic regression primarily used for?

💡 Hint: Think about what type of results logistic regression returns.

Question 2 Easy

What method is used to fit a logistic regression model in Python?

💡 Hint: This method is commonly used in machine learning to train models.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does logistic regression predict?

Continuous values
Binary outcomes
Both continuous and binary outcomes

💡 Hint: Remember what kind of outcomes we discussed.

Question 2

True or False: Logistic regression can only handle linear relationships.

True
False

💡 Hint: Think about the flexibility of logistic regression.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

If a logistic regression model predicts a 0.65 chance of passing for a student with 3 study hours and 70% attendance, what strategies would you recommend for this student? Provide at least three.

💡 Hint: Think about the inputs the model suggests improving.

Challenge 2 Hard

Create a scenario with three different student profiles that might yield different probabilities using logistic regression. What outcomes would you expect based on varying study hours and attendance?

💡 Hint: Focus on how input variations affect the predicted probabilities.

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