How does stochastic gradient descent differ from the classical one?
Machine Learning / AI
Why is it necessary to use the LEAD function to find future values by id in SQL?
On what basis should tables be joined in SQL?
How do you use search queries and user history to generate results in cold start?
Why does bagging work with trees, like in a random forest?
How to implement date sorting with millisecond precision in SQL?
How to use product categories to form relevant recommendations?
What error threshold should be used to stop training?
What is containerization and why is it needed?
How is resource allocation implemented in Docker?
Why is an analytical formula not used when solving a linear regression problem?
How to choose the threshold for auto-rejection and the threshold for manual moderation in the ad moderation task?
What are bias and variance, and what is reduced in a random forest?
How does Random Forest work?
How do hash join and merge join work?
How do you split data for cross-validation?
Tell us about Early Stopping: how does it work? Can it be applied in classical ML?
How is the proximity between word embeddings measured?