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What are the distinguishing features of the K-means and the Expectation-Maximization (EM) algorithm?

Machine Learning Engineer

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Did you come across this question in an interview?

  • Can you please elaborate on how K-means and the Expectation-Maximization (EM) algorithm differ?
  • Could you explain how the K-means and Expectation-Maximization (EM) algorithm differ in their approaches?
  • How do the K-means algorithm and the Expectation-Maximization (EM) algorithm contrast with each other?
  • In what ways do the K-means algorithm and the Expectation-Maximization (EM) algorithm differ?
  • What are the dissimilarities between the K-means algorithm and the Expectation-Maximization (EM) algorithm?
  • What are the distinguishing characteristics of K-means and Expectation-Maximization (EM) algorithm?
  • What are the distinguishing features of the K-means and the Expectation-Maximization (EM) algorithm?
  • What are the divergent qualities of K-means and Expectation-Maximization (EM) algorithm?
  • What is the difference between K-means and the Expectation-Maximization (EM) algorithm?
  • What sets the K-means algorithm apart from the Expectation-Maximization (EM) algorithm?

Interview question asked to Machine Learning Engineers interviewing at Venmo, Google, Intuit and others: What are the distinguishing features of the K-means and the Expectation-Maximization (EM) algorithm?.