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Interview questions by company and topic | SysRound

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60 questions

Showing 26–50

Machine learningEasy
Explain core ML concepts and metrics
Companies: Amazon
ML Fundamentals · Model Evaluation
Open workspace
Machine learningMedium
Explain core ML fundamentals and tradeoffs
Companies: Snapchat
ML Fundamentals · Neural Networks & Training
Open workspace
Machine learningHard
Explain Core ML Interview Concepts
Companies: Amazon
ML Fundamentals · Neural Networks & Training
Open workspace

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Machine learningMedium

Explain Data Collection Choices and Their Impact on Downstream Model Performance

Companies: xAI

ML Data Pipelines & Feature Stores · ML Fundamentals

Machine learningMedium

Explain dataset size, generalization, and U-Net skips

Companies: Apple

Computer Vision · ML Fundamentals

Machine learningMedium

Explain How L1 and L2 Regularization Change Linear-Model Coefficients

Companies: Point72

ML Fundamentals · Regression & Statistical Modeling

Machine learningMedium

Explain How Machine Learning Works Using a Kid-Friendly Analogy

Companies: Google

Communication & Stakeholders · ML Fundamentals

Machine learningEasy

Explain L1 vs L2 and ridge vs lasso

Companies: Upstart

ML Fundamentals · Regression & Statistical Modeling

Machine learningMedium

Explain Linear Regression Assumptions, Evaluation, and Feature Addition

Companies: Squarepoint

ML Fundamentals · Regression & Statistical Modeling

Machine learningHard

Explain logistic regression vs forests and boosting

Companies: Google

ML Fundamentals · Supervised Learning

Machine learningMedium

Explain metrics, regularization, and ablation studies

Companies: Microsoft

ML Fundamentals · Model Evaluation

Machine learningMedium

Explain ML and LLM fundamentals

Companies: Salesforce

ML Fundamentals · Model Evaluation

Machine learningHard

Explain ML and statistical modeling

Companies: Voleon

ML Fundamentals · Regression & Statistical Modeling

Machine learningHard

Explain Neural-Network Regularization and Dropout

Companies: Snapchat

ML Fundamentals · Neural Networks & Training

Machine learningEasy

Explain overfitting vs underfitting and fixes

Companies: LinkedIn

ML Fundamentals · Model Evaluation

Machine learningMedium

Explain overfitting, regularization, and LLM techniques

Companies: Amazon

AI Agents · ML Fundamentals

Machine learningHard

Explain overfitting, underfitting, and regularization

Companies: Pinterest

ML Fundamentals

Machine learningMedium

Explain PCA and L2 Normalization in Machine Learning

Companies: Experian

Feature Engineering · ML Fundamentals

Machine learningHard

Explain precision/recall and compute NN output

Companies: Coinbase

ML Fundamentals · Model Evaluation

Machine learningMedium

Explain the Margin View of Boosting Classification

Companies: C3 Ai

ML Fundamentals · Supervised Learning

Machine learningMedium

Explain variance reduction in random forests

Companies: LinkedIn

ML Fundamentals · Supervised Learning

Machine learningMedium

Explain What a Neural Network Is and How It Learns

Companies: Axq Capital

ML Fundamentals · Neural Networks & Training

Machine learningMedium

Handle p≈n linear regression with L1

Companies: Google

ML Fundamentals · Regression & Statistical Modeling

Machine learningMedium

Implement Gradient Descent and Explain Adam Updates

Companies: Akuna Capital

ML Coding · ML Fundamentals

Machine learningMedium

Implement Linear Regression with Batch Gradient Descent from Scratch

Companies: Pinterest

ML Coding · ML Fundamentals