A guide for novices in algorithm/data mining interviews -- machine learning algorithms that are often tested

As an algorithm or data mining engineer, the algorithm of machine learning is also a type of subject that is often tested, so here is a summary of some common test questions I encountered:

• 1 The principle and application scenarios
  of logistic regression (1) The principle of logistic regression
  (2) The difference between logistic regression and linear regression
  (3) The role of maximum likelihood function

• 2 SVM Algorithm Related
  (1) SVM Algorithm Principle
  (2) Types of SVM Kernel Functions, Application Scenarios, Advantages and Disadvantages
  (3) Outliers and their impact on model results

• 3 Decision tree
  (1) What are the conditions of the decision tree branch (the principle of whether the decision tree should be divided down)
  (2) The difference between decision tree and random forest
  (3) The concept and difference between variance and bias
  (4) There are many random forests The final processing method of the result of the tree
  (5) What types of decision trees are there
  ? (6) Reasons for overfitting of decision trees

• 4 The concept and significance of information entropy

• 5 Bernoulli distribution