1. "Explain the tradeoff between bias and variance." 2. "Explain what regularization methods are." 3. "Explain how to build a decision tree." 4. "Explain the difference between bagging models and boosting models." 5. "Explain the difference between GRU and LSTM models." 6. "Explain the difference between a CNN and RNN model." 7. "Explain how transforms work." 8. "Explain how BERT works."
Statistics Related Questions.
Database, machine learning modeling, oop
Some problem statements regarding NLP and Statistics.
Typical SQL questions (percentage and ranking) and data wrangling focused on aggregating granular data to make it ready for analytics
I didn't make it to the Interview Stage
Machine learning concepts and on SQL
What are you looking for in your next role
Boosting and bagging, projects done in the last
SQL related questions Infrastructure Design questions Product design questions Take-home test discussion
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