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2. ML/Data Coding 🤖

ML coding module may or may not exist in particular companies interviews. The good news is that, there are a limited number of ML algorithms that candidates are expected to be able to code. The most common ones include:

  • k-means clustering
  • k-nearest neighbors
  • Decision trees
  • Perceptron, MLP
  • Linear regression
  • Logistic regression
  • SVM
  • Sampling
    • stratified sampling
    • uniform sampling
    • reservoir sampling
    • sampling multinomial distribution
    • random generator
  • NLP algorithms (if that's your area of work)
    • bigrams
    • tf-idf

Sample codes