机器学习原理

题集来源:Alireza Dirafzoon(alirezadir)收录项目:AIMLInterviews查看原题集

题目目录

42 道原题
  1. What is machine learning and how does it differ from traditional programming?

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  2. What are different types of machine learning techniques?

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  3. What is the difference between supervised and unsupervised learning?

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  4. What is semi-supervised learning?

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  5. What are stages of building machine learning models?

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  6. Can you explain the bias-variance trade-off in machine learning?

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  7. What is overfitting and how do you prevent it?

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  8. Why and how do you split data into train, test, and validation set?

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  9. What is cross-validation and why is it important?

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  10. Can you explain the concept of regularization and its types (L1, L2, etc.)?

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