Q: Given a large dataset containing time-series data, design an efficient Python function to identify anomalies in real time. Discuss your approach to handle large data processing, including memory optimization, and outline which algorithms or statistical methods you'd use for anomaly detection
there were a bunch of statistical questions for example about p-values and experimental design as well as questions about XGB and Random Forest. They asked about the presentation and the style of presentation and what was on the slides as well.
If you do 100 coin flips, what's the probability of getting more than 50 heads?
What experience do you have with data analysis methods? Provide examples
Name any Python modules used for ML
Tell me about your self? Tell me about your prior experience? Why did you stop with your prior job?
What is Logistic Regression? Design a Recommendation System?
- Il mio percorso di studi, - Le mie conoscenze e/o competenze. - Esperienze pregresse - Quali programmi e pacchetti avessi utilizzato. Mi è stata poi presentata l'azienda e di cosa si occupava nello specifico il team.
What projects have you done? What was the most difficult project for you? (followed by questions on that). What are the models that you are very good at? A lot of basic data science concept questions.
How to solve X problem. Out-of-the-box ideas for certain issues. Background.
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