Intern Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"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."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"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."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"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."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"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 Logistic Regression, Backprop, and Adam
Walk through the mathematical foundations that connect logistic regression to modern deep-learning training. The interviewer expects you to write the ...
Evaluate NLP Classification Models
You are interviewing for a Data Scientist internship at Amazon. The interviewer asks you to walk through how you think about an NLP classification pro...
How would you forecast bike demand?
This question evaluates a candidate's competency in time-series forecasting, feature engineering, model selection, and evaluation for short-horizon de...
Build a Housing Price Prediction Model from Historical Data
You are given a historical dataset of residential real-estate transactions — sale records with property attributes, location information, and sale dat...
Explain Transformer and Fine-Tuning Basics
You are interviewing for an AI-focused engineering internship. Explain the following: 1. What is the difference between a transformer model and an emb...
Explain and test completion-rate gaps
In a food delivery marketplace, alcohol-related orders have a lower order completion rate than non-alcohol orders. Answer the following: 1. Propose se...
Daily Temperatures by Town: Linear Models to Predict NYC Temperature
Daily Temperatures by Town: Linear Models to Predict NYC Temperature You are given a dataset of historical daily temperature readings for New York Cit...
Fit logistic regression and return top features
You are given: - X: a 2D numeric array where each row is a feature and each column is an observation (shape: n_features x n_samples). - feature_names:...
Derive Linear Regression Solution
This question evaluates understanding of one-dimensional linear regression estimation, the statistical derivation of the mean squared error objective ...
Explain bias-variance and evaluate a classifier
You are interviewing for an Applied Scientist internship. Answer the following ML foundations questions. 1) Bias–variance - Define bias and variance i...
Predict a Company's Stock Price from Six Years of Web Search Logs
You are given a DataFrame containing the past six years of web search logs. Each row is a single search event with the following columns: | Column | T...
Explain Common Machine Learning Tradeoffs
The interview included a rapid-fire machine learning theory round. Be prepared to answer questions such as: - What are overfitting and underfitting? H...
Bounds on the Probability of Rain on at Least One Weekend Day
The probability that it rains on Saturday is $p$, and the probability that it rains on Sunday is $q$. Nothing is said about whether the two days are i...
Explain Medical AI Data and Evaluation
This question evaluates competence in medical conversational AI covering data sourcing and cleaning, leakage-aware dataset splitting, model choice (pr...
Four Fair Coins: Expected Payoff and Pricing Two Magic Wands
You play the following game: four fair coins are tossed at the same time. For every coin that lands heads, you are paid \$1. The interviewer walks you...
Explain metrics, regularization, and ablation studies
You are interviewing for an Applied Scientist role. 1) For a binary classification problem, explain the following and when you would use each: - Preci...
Pick a Number 1-100 Where the Higher Pick Pays a 10-Point Penalty: Optimal Strategy
Two players simultaneously each pick an integer from 1 to 100 (inclusive). The winner is decided as follows: take the larger of the two picks, subtrac...
Choose Between Precision and Recall for a Classification Decision
A binary classifier will support a real decision, and the model produces a probability score for each observation. Explain precision and recall, how t...
Predict Stock Prices from Google Search Data
You are given access to historical Google search data — relative search volume over time for arbitrary query terms — along with standard historical ma...
Decide Whether an LSTM Is Appropriate for Sequence Data
You are considering an LSTM for a prediction problem with sequential observations. Explain what an LSTM is designed to capture, how you would prepare ...