Upstart Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
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"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
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"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Explain L1 vs L2 and ridge vs lasso
Explain the differences between: 1. L1 vs L2 regularization (how they change the objective, geometry/intuitions, and typical effects on learned parame...
Implement PAVA spend-smoothing under no-borrowing constraint
Monotone Spending Plan via Isotonic L2 Regression (No-Borrowing) Context: You observe yearly discretionary income profit[1..65] (nonnegative reals) an...
Derive logistic regression objective and gradients
Context: Binary Logistic Regression You are given a binary classification dataset {(x_i, y_i)}_{i=1}^m with labels y_i ∈ {0, 1}. The model uses the si...
Design a Real-Time Personalized Ad Selection System
End-to-End ML System Design: Real-Time Ad Selection Context You need to design a real-time, data-driven ad selection system that personalizes ads for ...
Leverage Existing Model for Low Credit Score Applicants
Expanding a Credit-Risk Model to a New Score Band Scenario Your current probability-of-default (PD) lending model was trained only on applicants with ...
How to Architect a Personalized Ads Serving System
Full-Funnel Ads Serving System Design Scenario You are asked to architect a full-funnel advertising platform that serves personalized ads to users on ...
Design a Regression Model for Robust Extrapolation Performance
Scenario Onsite machine-learning exercise: your task is to build a regression model using only numerical features that not only fits training data but...
Design Push-Notification System for Airport Surge Pricing
Designing Airport Surge Push Notifications for Drivers Context You are building a real-time system for a ride-hailing platform. When an airport experi...
Address Missing Income Bracket in California Housing Data
ML Case: Missing Lowest-Income Bracket in California Housing Data Context You're building a supervised model (regression) to predict California housin...