Questions d'entretiens - Data scientist

Talked about my work background and what type of work I was looking for. It was more of a discussion to assess my fit with the company and the type of work that I could be doing.

The key in these questions is to cover the fundamentals, and be ready for the back-and-forth with the interviewer. Might be worth doing a mock interview with one of the Shopify or ex-Shopify Data Analyst experts on Prepfully? They give real-world practice and guidance, which is pretty helpful. prepfully.com/practice-interviews

It depends; the model could be overfitting, but they are expecting an answer related to the dataset being imbalanced.

Also, consider that for most classification problems accuracy is not the best metric to look at. We should rather look into confusion matrix (recall & precision) as well as AUC. So better to clarify whether we are talking about a classification or regression model.

no

Indeed, it occupies space in proportion to the number of rows contained.

The HR contractor provided examples and gave me time to answer them. I answered them honestly. I gave them examples of various work assignments I had at school and they seemed satisfied with my answers.

This is a fake post created by a temporary HR employee that is attempting to create a positive reference for herself.

Use subqueries, views as necessary. Try to break down the complex query into small pieces, and achieve each piece step by step.

The key in these questions is to cover the fundamentals, and be ready for the back-and-forth with the interviewer. Might be worth doing a mock interview with one of the Wattpad or ex-Wattpad Data Analyst experts on Prepfully? They give real-world practice and guidance, which is pretty helpful. prepfully.com/practice-interviews

def ques_remover(N): for e in range(N): if e%2 == 0: yield ‘110100’ else: yield ‘111100’

Then u can iterate over the generator function

2) Model complexity Vs training time; precision vs recall

bias vs variance