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Could you describe your experience with A/B testing?
Do you know what an A/A test is and why we need it?
Suppose an A/B test shows statistically significant results for 5 out of 100 randomly selected metrics after two weeks. Should we switch to the new version? Why or why not?
а вы какой-то ABT-тест проводили, ты говоришь, что просто разделили model, то есть как дизайнили ABT-ст?
А, ну, как-то оценивали перед БТС там, например, сколько вам надо абонентов в группу Б добавить?
What infrastructure have you used for model training: internal clusters or cloud services?
Have you built ML pipelines for training neural networks?
Do you have experience with FastAPI and building REST APIs?
Do you have experience with big data technologies such as Hadoop, Spark, or PySpark?
Given a CSV of exchange trades with timestamp and volume, find the time intervals with the highest trading volume. How would you determine the optimal window size?
A file of exchange trades does not fit in RAM. How would you find the interval with the highest volume in one pass?
A stream of exchange packets includes send and receive timestamps. How would you detect latency anomalies?
What data volumes and model training times have you worked with? Do you have experience with parallelism?
What experience do you have with Hadoop, Spark, and MapReduce?
Describe your experience with PySpark and distributed computing. How does MapReduce work?
Какие метрики бы предложили для оценки дрифта данных? И для вторичной валидации моделей каждый раз бы их использовали?
И какие риски мы можем переобучить на каких-то форты данных?
Под что может больше строковые базы данных пригодиться?
А уверенность, это что за такая штука такая? Как ее добыть из данных?
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