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Implement linear and logistic regression

UberMachine Learning Engineer · Technical Screen
MediumMachine Learning EngineerTechnical ScreenMachine Learning

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This question evaluates understanding and hands-on implementation of linear and logistic regression, testing competencies in prediction functions, loss formulation, gradient computation, gradient descent training, regularization, and model selection within the Machine Learning domain (supervised learning and statistical modeling).

Explain and implement linear regression and logistic regression from scratch.

Your answer should cover:

  • The prediction function for each model
  • The loss function
  • How to compute gradients
  • How training works with gradient descent
  • Regularization
  • The main differences between the two models and when to use each one