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."
Database, machine learning modeling, oop
Statistics Related Questions.
Some problem statements regarding NLP and Statistics.
Machine learning concepts and on SQL
Data science assessment: Should Zillow's sales team charge a flat rate per community or a rate per leads that each community receives?
1. Resume-based questions. 2. Take-home test for business entity resolution algorithm.
Me fale sobre um projeto e como vc solocionou o problema
How many years of experience with LLMs do you have?
They asked me about the type of work I did, specific basic questions on programming and data science.
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