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Since the interview was purely based on your current work experience and follow up from that so my interview questions were based on the same. Below are my questions(may help you estimate yours): There is no intro in the call, straight ques-ans round. 1)Let's begin with your experience with AWS. Can you tell me about a project where you utilised AWS services and which services you found the most important for your project's success. 2) Shifting focus to your NLP experience, could you elaborate on how you have applied NLP techniques in your project, particularly any challenges you faced in language processing and how you overcame them. 3) Given your experience in Python, can you tell us how you have used Python in conjunction with NLP libraries to preprocess and analyse text data on your project. 4) Regarding your work with BERT and other transformer model, could you specify specific incidence where you applied BERT to a problem and how you fine tuned the model to serve your specific use case? 5) How did you specifically fine tuned BERT to your use case? How did you handle the training doc and what were your outcomes after applying BERT to your text data. 6)Elaborate on fine tuning process, how did you decide the hyperparameters and what kind of improvements did you see after fine tuning compare to before. 7)Can you tell me about a time where you had to optimise the model performance post deployment, perhaps in cases to data distribution or user feedback, how did you approach the issue and ensure the model remained accurate and relevant?
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AI Data Scientist

Interviewed at Mercor

4★
Jan 24, 2024

Since the interview was purely based on your current work experience and follow up from that so my interview questions were based on the same. Below are my questions(may help you estimate yours): There is no intro in the call, straight ques-ans round. 1)Let's begin with your experience with AWS. Can you tell me about a project where you utilised AWS services and which services you found the most important for your project's success. 2) Shifting focus to your NLP experience, could you elaborate on how you have applied NLP techniques in your project, particularly any challenges you faced in language processing and how you overcame them. 3) Given your experience in Python, can you tell us how you have used Python in conjunction with NLP libraries to preprocess and analyse text data on your project. 4) Regarding your work with BERT and other transformer model, could you specify specific incidence where you applied BERT to a problem and how you fine tuned the model to serve your specific use case? 5) How did you specifically fine tuned BERT to your use case? How did you handle the training doc and what were your outcomes after applying BERT to your text data. 6)Elaborate on fine tuning process, how did you decide the hyperparameters and what kind of improvements did you see after fine tuning compare to before. 7)Can you tell me about a time where you had to optimise the model performance post deployment, perhaps in cases to data distribution or user feedback, how did you approach the issue and ensure the model remained accurate and relevant?

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