What should be done with a dataset before training a model?
Machine Learning / AI
What metrics are used to evaluate the quality of the rating prediction model for advertising campaigns?
What can be done to speed up the function's performance?
Tell me more about the Root Cause Analysis (RCA) project — what it is and how the system was implemented.
How to display information about how much video memory each process occupies in Linux?
Can linear regression be used in cases of sample bias?
How to understand when to stop feature selection?
Are there any restrictions due to working with personal data?
Why can't accuracy be directly optimized?
How to determine which of two databases to use based on classification results?
What are the methods of text processing in NLP from simple to modern neural networks?
What are stale embeddings and how to deal with them?
What are the existing classification quality metrics?
How does the DevOps team provide feedback?
Write a Python program: create a 1000x1000 matrix, fill rows with Fibonacci sequence, square the elements of the secondary diagonal. Time: 2 minutes.
Will the code work with an empty string?
Within what range are the hyperparameters of the model set?
Write a function that returns the character with the maximum number of consecutive repetitions in a string.
What feature selection methods exist?