Statistics, Coding, and Data Science
Applied Scientist Interview Questions
1,179 applied scientist interview questions shared by candidates
ask for the computer vision algorithms like ResNet block, how FRCN works, and how yolo works, and what is their difference, after then we did a quick leetcode test (rotate the 2D matrix 90 degrees).
Explain how logistic regression works. Describe a recent ML project I did.
Describe your previous projects? What did you like in them?
Explain a machine learning project you’ve worked on. What were the challenges, and how did you address them? How would you approach building a recommendation system for a new product? Discuss the trade-offs between different machine learning algorithms (e.g., decision trees vs. neural networks). How do you handle missing data in your datasets? Explain the concept of regularization and why it’s important.
How does a Transformer work
It wasn’t leetcode style question
Explain regularisation procedures in deep neural nets
1. Leadership principle questions (around 2) with follow-up questions. 2. Basic ML questions. 3. ML use case problem with follow-up questions.
- How to handle difficult situations - How to handle different opinions between colleagues - How a CNN works - How a RNN works - Did you work with Transformers? What is Attention? - Summary metrics for NLP - CODING: Two sum but with multiplication actually - How a BiLSTM works - Metrics for regression BONUS INTERVIEW WITH OTHER TEAM (more friendly) -Bagging and boosting -Forecasting example -Computational difference between XGBoost and Random Forest
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