Underfitting, Overfitting, Case study, Statistical analysis
Machine Learning Consultant Interview Questions
8,221 machine learning consultant interview questions shared by candidates
Boosting, validation metrics, cross-validation, imbalanced datasets, accuracy, F1 score, CNN, Docker, Kubernetes
Given Dover's current client onboarding flow, how can we improve it with the help of machine learning.
Everything related with my experience and career expectations.
In the coding task I was asked to do a simple leetcode problem first, then a git merge and manual resolution of conflicts, and then the final part was a data analysis section. For the data analysis I had to download a dataset from Kaggle and visualise some trends in it.
Could you explain one of the latest data projects you have worked in?
The technical question was a fairly basic data processing question, easily solved using Pandas.
1. Describe the bias variance tradeoff. 2. How would you measure the performance of a classifier? 3. What is an example of a problem where you would favor recall over precision and vice versa.? 4. Describe the main idea behind boosting along with some well known algorithms such as adaboost and xgboost. 5. Describe several options for embedding text data into a feature along with pros and cons of each. 6. Describe your favorite sorting algorithm
This is out of context, but one question I wrote down was, "What would you tell a CIO to ask a vendor when evaluating an off-the-shelf AI product?"
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