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. How Do You Handle Missing or Corrupted Data in a Dataset

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  2. What is a decision tree and how does it work?

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  3. Can you explain logistic regression?

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  4. Can you explain the K-Nearest Neighbors (KNN) algorithm?

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  5. Compare K-means and KNN algorithms.

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  6. Explain decision-tree based algorithms (random forest, GBDT)

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  7. What is gradient descent and how does it work?

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  8. Can you explain the support vector machine (SVM) algorithm? what is Kernel SVM?

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  9. Can you explain neural networks and how they work?

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  10. What is deep learning and how does it differ from traditional machine learning?

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