Discussion questions S2

.pdf

School

Georgia Institute Of Technology *

*We aren’t endorsed by this school

Course

6501

Subject

Mechanical Engineering

Date

Apr 3, 2024

Type

pdf

Pages

1

Uploaded by EarlMorning13539

1. What is the purpose of cross-validation in machine learning, and how does it help in model evaluation? 2. Discuss the concept of regularization in the context of linear regression. How does regularization prevent overfitting? 3. Explain the fundamental principles of A/B testing and its applications in business decision-making. 4. Describe the concept of unsupervised learning and provide examples of clustering and dimensionality reduction techniques. 5. Discuss the bias-variance tradeoff in the context of machine learning models. How does it impact model performance? 6. Explain the difference between sensitivity and specificity in the context of classification models. Why are these metrics important? 7. Discuss the role of optimization in the context of linear programming. Provide a practical example where linear programming can be applied. 8. What are the key components of a decision support system, and how can it aid in managerial decision-making? 9. Describe the concept of ensemble learning. How do techniques like bagging and boosting improve the performance of machine learning models? 10. Explain the importance of feature engineering in predictive modeling. Provide examples of common feature engineering techniques.
Discover more documents: Sign up today!
Unlock a world of knowledge! Explore tailored content for a richer learning experience. Here's what you'll get:
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help