1) Build a production ready API with an ML model behind. 2) Explain the different optimization algorithms in DNN. 3) What are kernels and what is their use? 4) Why CNN's are translation invariant? 5) Review a Python module suggesting changes. 6) How would you regularize Random Forests? 7) How to make linear regression and Random Forests robust to outliers?
Describe a global scale ML project
ML and DL basic question, NLP, LLM. Talking about the projects you have done in details.
DSA question was given an array of integers, return another with product of elements except the element at index
AI/ML coding: NLP use case that involves walking through how you would calculate word frequency (TFIDF) then what's the best method to measure vector similarity. **Job description does not mention NLP**
A project on NLP within a week
1. Walk me through your experience? What projects did you work on? Hold on, let me interrupt you before you finish your first sentence.
Leetcode non-ML questions about strings. In fact, there were no ML coding questions.
NLP questions. ML related to cloud.
Behavioral questions, like tell me about something you build or a conflict in a workplace.
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