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Learning Engineer Interview Questions
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ML Practical: Design a system for fraud detection (when the customer is fraudulent).
Assessment: 3 parts involving coding, code review, and creating a design doc for a problem (estimate order processing time).
What is Regularisation ? How it works ? Why is it needed
What ML architectures worked the best on this specific asset?
Machine Learning Basics Large Language Models GenAI Applications Resume Discussion DSA/Leetcode ML Lifecycle
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Explain what a transformer neural network is? What would you do in the first few months of the role?
1. Why are you interested in this position? 2. Talk about a situation where customer feedback is important.
Why you used kafka locally and not deployed it in the cloud? How you could have solved the problem in a different way?
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