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Interview questions by company and topic | SysRound

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60 questions

Showing 51–60

Machine learningMedium
Implement MSE Loss and Linear Regression from Scratch
Companies: Indeed
ML Coding · ML Fundamentals
Open workspace
Machine learningMedium
Minimizing a Convex Quadratic: Closed Form and Iterative Optimization Algorithms
Companies: Uber
ML Fundamentals
Open workspace
Machine learningEasy
ML Basics Check: Bayes' Rule, Forward-Pass Arithmetic, KNN and Transformer Concepts
Companies: Netflix
ML Fundamentals · Neural Networks & Training
Open workspace

Page 3 of 3

Machine learningHard

Predict bike demand and avoid overfitting

Companies: Two Sigma

Feature Engineering · ML Fundamentals

Machine learningHard

Prevent Vanishing Gradients in Deep Networks

Companies: Pinterest

ML Fundamentals · Neural Networks & Training

Machine learningMedium

QUANTITATIVE RESEARCHER

Companies: Jane Street, JPMorgan, Optiver, Point72 +1

Feature Engineering · ML Fundamentals · ML System Design · Model Evaluation

Machine learningHard

Reduce overfitting under constraints

Companies: Boston Consulting Group

ML Fundamentals · Supervised Learning

Machine learningMedium

What Cross-Validation Reduces: Bias, Variance, Type I or Type II Error

Companies: Headlands

ML Fundamentals · Model Evaluation

Machine learningMedium

Which Regularization Penalties Set Model Coefficients Exactly to Zero

Companies: Pinterest

ML Fundamentals · Regression & Statistical Modeling

Machine learningMedium

Write the Cross-Entropy Loss and Compute Precision, Recall and F1

Companies: ByteDance

ML Fundamentals · Model Evaluation