Mid‑Level Test of Core ML Algorithms

Test your knowledge of core machine learning algorithms with eight challenging items.

machine learningneural networksalgorithmsfeature engineeringmodel evaluationclusteringdecision treesgradient descentunsupervisedsupervised learning
Difficulty:MEDIUM

Quiz Details

Questions8
CategoryArtificial Intelligence & Machine Learning
DifficultyMEDIUM
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Quiz Questions

Answer all questions below and test your knowledge.

  1. 1

    Which algorithm iteratively updates parameters to minimize a differentiable loss using the steepest slope?

    Question 1
  2. 2

    In a decision tree, which impurity measure calculates the probability that a randomly chosen element would be incorrectly labeled if it were randomly labeled according to the distribution of labels in the node?

    Question 2
  3. 3

    Which clustering technique partitions data by assigning points to the nearest of a predetermined number of centroids and then recomputes centroids until convergence?

    Question 3
  4. 4

    Which supervised method constructs a hyperplane that maximizes the margin between two classes in a high‑dimensional feature space?

    Question 4
  5. 5

    Which algorithm builds an ensemble by training successive learners on the residual errors of the previous model?

    Question 5
  6. 6

    Which method estimates the probability of a class by applying Bayes’ theorem assuming feature independence?

    Question 6
  7. 7

    Which neural architecture processes data sequentially, maintaining a hidden state that captures information from previous time steps?

    Question 7
  8. 8

    Which dimensionality reduction technique projects data onto orthogonal axes that capture the greatest variance?

    Question 8

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