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How do you perceive the role of DMatrix in XGBoost, and how does it differ from other gradient boosting data structures?

For neural networks, is the vanishing gradient concern more frequent towards the network's input or its output?

Suppose you have two tables, "orders" and "customers", where "orders" contains information about orders and "customers" contains information about customers. Write an SQL query that calculates the average order value for each customer who has made at least 3 orders in the last month, and only includes customers who are located in the United States. The query should require a join between the two tables.

Is there a particular reason you are applying to VeriSign?

What do you think does VeriSign values in its employees?

Can you discuss your real-world experience with NLP and its use in recommender systems?

It's a well-known issue that gradient problems can hamper deep learning productivity. How do you usually handle them?

How would you explain a median and what techniques would you use to compute it from an oversized dataset?

What method do you use to identify and extract every instance of an English word from a given string of characters?

Tell us about some unpleasant feedback that you received?