Machine Learning in Astronomy — MCQs

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1. What is the primary role of machine learning in astronomy?





2. Which astronomical data type is often analyzed with machine learning?





3. Which technique helps classify galaxies in large surveys?





4. Neural networks are especially useful for:





5. Which method is commonly applied for anomaly detection in astronomy data?





6. Machine learning is essential in time-domain astronomy because it:





7. Which type of machine learning helps in identifying exoplanets from light curves?





8. Decision trees are used in astronomy for:





9. What is overfitting in astronomical ML models?





10. Convolutional Neural Networks (CNNs) are widely applied to:





11. Which survey used ML for automatic classification of millions of galaxies?





12. What is the purpose of dimensionality reduction in ML astronomy?





13. K-means clustering in astronomy is often used for:





14. Which ML approach is best for predicting star lifetimes?





15. Deep learning is especially powerful in astronomy for:





16. Which ML technique detects exoplanets in noisy data?





17. Why is labeled data important in supervised learning for astronomy?





18. Random forests are often applied to:





19. Which ML method is most suited for real-time transient detection?





20. Feature extraction in astronomical ML involves:





21. Which ML model is used to detect gravitational wave signals?





22. Which learning method identifies hidden structures in unlabeled data?





23. ML algorithms reduce human bias in astronomy by:





24. Which ML technique improves telescope scheduling?





25. Support Vector Machines (SVMs) are often used for:





26. Neural networks can be trained to distinguish:





27. Which ML method helps predict solar flares?





28. Semi-supervised learning is useful when:





29. Why is cross-validation important in ML astronomy?





30. Which ML technique enhances galaxy morphology studies?





31. The Kepler mission data was analyzed with ML to find:





32. Reinforcement learning in astronomy is applied to:





33. Which ML method helps clean noisy astronomical spectra?





34. Which is a challenge in applying ML to astronomy?





35. Why is interpretability important in astronomical ML?





36. Which ML method aids in radio astronomy data analysis?





37. Data augmentation in astronomy ML helps to:





38. What role do GPUs play in astronomy ML?





39. Which ML application aids in classifying radio signals as extraterrestrial or noise?





40. Active learning is valuable in astronomy because:





41. Which ML approach helps forecast cosmic ray events?





42. Which survey applied ML to classify millions of variable stars?





43. Why is anomaly detection important in astronomy?





44. Transfer learning in astronomy ML allows:





45. Which ML approach was used to detect gravitational lensing arcs?





46. Which ML framework is commonly used in astronomy research?





47. What does unsupervised clustering reveal in astronomy datasets?





48. Why are large astronomical surveys ideal for ML?





49. Citizen science projects like Galaxy Zoo benefit from ML by:





50. What is the ultimate aim of ML in astronomy?





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