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Supervised Learning

  • Q. What are the advantages and disadvantages of Random Forest?
  • Q. What are the key hyperparameters for a Random Forest model?
  • Q. Explain the concept and working of the Random Forest model
  • Q. What is Bagging? How do you perform bagging and what are its advantages?
  • Q. What are the advantages and disadvantages of Decision Tree model? 
  • Q. What is CART?
  • Q. How does pruning a tree work?
  • Q. Explain the concept of Linear Regression
  • Q. How does a decision tree create splits from continuous features?
  • Q. Explain the difference between Entropy, Gini, and Information Gain
  • Q. What is a Decision Tree? Explain the concept and working of a Decision tree model
  • Q. Regression vs. Classification
  • Q. What is Classification?
  • Q. What is Supervised Learning?
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  • Deep Learning (52)
    • DL Architectures (17)
      • Feedforward Network / MLP (2)
      • Sequence models (6)
      • Transformers (9)
    • DL Basics (16)
    • DL Training and Optimization (17)
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  • Supervised Learning (115)
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      • Classification Evaluations (9)
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      • Other Classification Models (9)
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Other Questions in Supervised Learning
  • How does SVM adjust for classes that cannot be linearly separated?
  • What is Bi-Clustering? What are possible use cases of it?
  • How to perform Standardization in case of outliers?
  • What is a Multilayer Perceptron (MLP) or a Feedforward Neural Network (FNN)?
  • Distinguish between a Weak learner and a Strong Learner
  • What are the pros and cons of parametric vs. non-parametric models?
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