Practice Enabling Scientific Discovery and Knowledge Extraction - 3.1.4 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
K12 Students

Academics

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

Academics
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 skillsβ€”perfect for learners of all ages.

games

3.1.4 - Enabling Scientific Discovery and Knowledge Extraction

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does LIME stand for?

πŸ’‘ Hint: Look for keywords starting with each letter.

Question 2

Easy

What does SHAP help to explain in machine learning?

πŸ’‘ Hint: Think of game theory terms.

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 is the primary goal of Explainable AI?

  • Improve prediction accuracy
  • Enhance interpretability
  • Reduce computation time

πŸ’‘ Hint: Consider why scientists need to trust AI.

Question 2

True or False - SHAP is exclusively for explaining linear models.

  • True
  • False

πŸ’‘ Hint: Reflect on what 'model-agnostic' means.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Develop an argument for or against the necessity of XAI in AI systems used in criminal justice.

πŸ’‘ Hint: Reflect on the implications of accountability in society.

Question 2

Analyze a situation where model transparency could lead to better scientific outcomes in climate modeling.

πŸ’‘ Hint: Think about how understanding influences decisions in science.

Challenge and get performance evaluation