- 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
Explain gradient descent, batch norm, how to accelerate, how to parallel, how to change the batch size when parallel and how to save memory for running.
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.
Q: Questions related to my published paper.
Why Amazon? Mention one challenge.
Science depth Science breath Leadership principals Coding
What is variance and bias tradeoff
Star methods for Leadership principles, use examples.
Create permutations of a string
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