Machine Learning / AI
How are machine learning algorithms trained and what is their main trick?
How to implement key validation with negative and matching values for mirror points?
Why is the learning rate needed and what does it affect?
What methods for combating overfitting exist and how do they work?
Is it possible to find a solution faster than O(n^2)?
What reasons can lead to different values of average daily visits to a web service among different analysts?
What are your knowledge of probability theory?
Why are metrics other than accuracy needed?
What data sources for ML have you integrated (DWH, Kafka, S3)?
How to determine the direction of x change during gradient descent?
Implement a solution to the problem in Python.
What is RAG? Can you tell me?
What does the MLOps pipeline include from training to deployment?
What is A/B testing? How to apply it in the context of model comparison?