Medium to Complex Algorithm Questions. Basic ML questions
Data Science Consulting Interview Questions
40,344 data science consulting interview questions shared by candidates
¿Te has encontrado con un problema de inclusión social en ambiente laboral? (explicación, solución)
very primary question in python
1. How do you use NN to reduce dimensionality? 2. Can you model time series as a linear regression model? 3. a) Can you use resampling methods like bagging to estimate the max of a population? b) Why is bagging a variance reduction scheme? 4. Why is the use of minibatch to minimize a function computationally more efficient than any other methods? 5.Gambler's ruin problem. 6. Assume that in a time series, some data are missing. How do you handle that? A. average out the existing values. Okay, so you want to average out the existing values, but how do you define the the new time series as a single function? A. Use characteristic or indicator function.
How can you find percentile? Write code
SoftDev : Python (I chose), you have an array of string sorted but with empty strings (e.g. ["abc","","","","cef","","","dej,""] and you want to know if an other string is in this array. How to do it with a complexity of O(log n) in general case ? Then how to find how many times it appears in this array ?
Moderate level questions on the decisions to apply a particular ML algorithm on a dataset, (What they're looking for is a reasoning that factors in everything like inference time, results examinability(XAI or SHAP) and not just what algorithm will be the most accurate on a dataset. )
Quels sont vos motivations pour intégrer notre équipe
¿Tienes experiencia en sólida en Azure Databricks, BI, BigData, DevOps, MLOps, paradigmas Data Mesh/Data Fabric?
How would you benchmark an object detection model acting over a vide stream? For example, a model that is meant to detect alcohol consumption scenes in a video.
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