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
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics

Grades

Grade 8 Grade 9 Grade 10 Grade 11 Grade 12

Curriculum

CBSE ICSE IB
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Typing
Memory
Math
English Adventures
Knowledge

9.5 - Step 4: Build the Model – Logistic Regression

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take mock test.

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

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.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

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.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

Question 2

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.

Challenge and get performance evaluation