Can't recall the specific questions and they varied by individual. The worst questions were from someone who grilled me on steps of analyses and actually said "pretend you are walking to your computer. Now tell me how you are going to analyze your data." Others were more innocuous but there was still an element of testing ad nauseum.
Why do you want to join dunnhumby?
a case study to prepare at home, then present it to the team , no coding needed just slides
Difference between correlation and covariance.
Self introduction and my work experience.
Coding test task 1: pandas on what looked like a phone company database (super lengthy) Coding test task 2: lasso, ridge and elastic net Screening: questions about past experience
Machine Learning case study interview. Open ended question with no right answer - they want to evaluate your ability to walk through a solution
Describe the process to implement a model to detect if there was a person on an image that wears glasses, from the begging (data) to the end (metrics)
🔹 1. Conceptual Questions (Beginner–Intermediate) ❓ Supervised vs. Unsupervised learning What is the difference between supervised and unsupervised learning? Give examples of real-world problems for each. ❓ Model Understanding What is overfitting and underfitting? How do you prevent overfitting? What is the bias-variance trade-off? What are precision, recall, F1-score, and when do you prefer one over another? ❓ Algorithms How does a decision tree work? What is the difference between logistic regression and linear regression? How does K-nearest neighbors (KNN) work? What is regularization (L1 vs. L2)? 🔹 2. Intermediate to Advanced Topics ❓ Ensemble Methods How does random forest work? What is gradient boosting (e.g., XGBoost, LightGBM)? Difference between bagging and boosting? ❓ Neural Networks What is backpropagation? What are activation functions and why are they important? Difference between CNNs and RNNs. What is dropout, and why is it used? ❓ Optimization What are common optimizers in deep learning? How does stochastic gradient descent (SGD) differ from batch gradient descent?
shortest sub array to sort
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