take home data science homework is free form, you are given a pipeline with a bunch of classifiers that'll predict whether a user is retained or not based on swiping activity, you're told to add whatever you want to the pipeline to showcase your skills the tools are the traditional sklearn/numpy/matplotlib etc and the algos involved are regression/xbgoost/other voting algos
Test technique à faire chez soi
What did i do in the last project?
You need to train one model to detect two classes A & B but 50% of the training dataset was labelled only with class A and 50% only with class B. How do you train this model?
Could you describe in detail your research projects? What machine learning models/tools did you use? What was the motivation of using these tools?
How do you implement feature selection in text classification?
Are you okay being paid below the market salary for Machine Learning Engineer role?
Why did you choose Cohere Health?
During system design interview I was asked to implement LRU cache
What is the difference between data and big data and how does hadoop form a prerequisite to deal with 3 Vs of big data.
Viewing 761 - 770 interview questions