Qual è il parametro di regolarizzazione nella regressione logistica e come lo si calibra
Junior Scientist Interview Questions
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Differenza tra supervised e unsupervised models, esempi di modelli in ciascuna categoria
Nel colloquio tecnico, dopo una breve presentazione, mi è stato chiesto di spiegare qualche algoritmo di machine learning e di implementare una funzione su python
¿Qué me cuentas de ti y que motivaciones tienes? ¿Cuáles son tus facetas mas destacadas y un punto débil? Dime una situación donde hayas propuesto algo innovador en tu trabajo o en la universidad.
D: Explain how you used your Data Science skills in the context of the Master's thesis, with a focus on the main topic (PCA).
Explain your projects which is mentioned in your resume Have a Knowledge in data science domain and statistics
Relier chaque librairie à son utilisation (Numpy, MatplotLib, Scikit Learn,…)
Based on your background, they will either ask questions from Statistics (in particular, Bayesian Statistics) or questions pertaining to programming. The former will usually include full-fledged numericals, for example, you may be asked to find the probability of false positives in a new clinical trial given some data using Bayes' Theorem. You may also be asked basic definitions such as "Intuitively describe what the "likelihood" of an event is and how it differs from simple probability." Both my interviewers were kind and guided me when I got stuck. They do not need you to know the answers in advance, just be able to reason and discuss well and also be able to use a wide variety of tools to tackle a problem.
Explain Bayes Theorem and explain Central Limit Theorem.
machine learning, time series, sql
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