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Go Back1. What is an epoch?
2. What are some of the ethical considerations that are taken into account when designing machine learning algorithms?
3. What is the event commonly referred to as the singularity?
4. What is deep learning?
5. Have you ever used TensorFlow?
6. Do you know any libraries that are useful for machine learning?
7. Why is python often used for machine learning?
8. What is a loss function? How does this differ from a cost function?
9. What is the F1 score? And how is it calculated?
10. What is normalization? And what problem does it solve in machine learning?
11. What is regularization?
12. What is underfitting?
13. How can you prevent or avoid overfitting?
14. What is overfitting?
15. What is Machine Learning? What is the difference between Artificial Intelligence and Machine Learning?
16. What is a neural network?
17. What is a perceptron?
18. What is meant by K-means clustering? Is this a supervised or unsupervised machine learning technique?
19. What is a random forest? And what is the bagging method?
20. What are some of the advantages and disadvantages of using decision trees?
21. What are decision trees?
22. When might you use classification and not regression?
23. What is the difference between classification and regression?
24. What is Linear Regression and what can it be used for?
25. What is the difference between supervised and unsupervised Machine Learning?
26. What is Data Labeling?
27. Provide some examples of well known and commonly used Machine Learning Algorithms? please identify if they are supervised or unsupervised
28. What can Machine Learning be used for?