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Explain me a hash table?
Tell me what is precision and recall?
Tell me how would you implement a recommendation system for our company's users?
Tell me what are the last machine learning papers you've read?
Explain me what is machine learning?
Tell us how do you handle missing or corrupted data in a dataset?
Tell me how much data will you allocate for your training, validation and test sets?
Tell me how a roc curve works?
Tell me what is the most frequent metric to assess model accuracy for classification problems?
Tell us why is “naive” bayes naive?
Do you know what's the “kernel trick” and how is it useful?
Tell us when should you use classification over regression?
Tell us when will you use classification over regression?
Tell us how do you ensure you're not overfitting with a model?
Tell me what is supervised versus unsupervised learning?
