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Machine Learning Flashcards

6 cards from real Artificial Intelligence practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 6 Machine Learning flashcards as text
  1. Which algorithm is a non-parametric method that classifies new points based on the majority class of their nearest neighbors?

    Answer: K-Nearest Neighbors

    K-Nearest Neighbors classifies a point by looking at the k closest training examples and using a majority vote.

  2. What is cross-validation used for in machine learning?

    Answer: To estimate model performance on unseen data

    Cross-validation partitions data into folds to provide a reliable estimate of how the model generalizes.

  3. Which ensemble method builds multiple decision trees and averages their predictions?

    Answer: Random Forest

    Random Forest builds many decision trees using random subsets of data and features, then averages results.

  4. What is 'feature engineering' in the machine learning pipeline?

    Answer: Creating or transforming input variables to improve model performance

    Feature engineering involves creating, transforming, or selecting input variables to make patterns easier for a model to learn.

  5. Which gradient boosting library is widely used in US industry competitions and known for speed?

    Answer: XGBoost

    XGBoost is an optimized gradient boosting library that is fast, scalable, and popular in competitions like Kaggle.

  6. What does 'learning rate' control in gradient descent optimization?

    Answer: The step size taken in the direction of the negative gradient

    The learning rate determines how large each parameter update step is during gradient descent.