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This is a medium difficulty Machine Learning question, commonly asked during Technical Screen rounds at Uber.

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This question is commonly asked for Machine Learning Engineer candidates at Uber during technical interviews.

Implement linear and logistic regression

Last updated: Mar 29, 2026

Quick Overview

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).

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Implement linear and logistic regression

Uber

Mar 1, 2026, 12:00 AM

mediumMachine Learning EngineerTechnical ScreenMachine Learning

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

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