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Machine Learning Interview Questions
8,199 machine learning interview questions shared by candidates
The problem is general and designed according to the app in the company. Define and narrow down the scale of the problem. Then dive deep through the general process of the general system design problems.
There're three programming questions (with few details about pretended results) where I develop Python scripts importing the NumPy library. The remaining one is more theoretical implying a code explanation. All of them are related to the Computer Vision field.
Explain what PCA is to a developer.
- Please briefly introduce yourself and your background.
1) Can you explain the difference between the Random Forest and XGBoost algorithms? 2) What are L1 and L2 regularization techniques, and which one would you use for feature selection? 3) What are the different model deployment options available in Amazon SageMaker? 4) How would you monitor a deployed model on SageMaker to ensure its performance over time? 5) Can you tell me about a research paper that you found particularly inspiring or impactful? What made it stand out to you?
Core concepts about machine learning. Deep dive into previous ML-related projects and experiences
Most interviews were technical. First interview was high-level algorithmic question about designing an algo to find closest point in 2D map with limited informations, and to reason on the complexity of the algo I come up with.
Questions related to basic ML
Senior ML researcher role - leetcode + basic ML questions, applied research discussion, systems design discussion, each 1 to 1.5h Squad lead role - leadership interview 1h
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