Daten Interview Questions

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1. What's the relationship between PCA and k-means clustering? 2. What are the requirements for a matrix to represent a kernel? What happens if we run SVM using a 'kernel' that does not satisfy these requirements? 3. Problems using Python lists and dictionaries 4. SQL joins, aggregates (count, sum, avg), and cases 5. If you were given a dataset with [X] features (may be numerical, categorial, etc.) and you want to build a model (to determine fraudulent transactions, say), how would you determine which features are best to use in the model?
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Data Scientist

Interviewed at Palo Alto Networks

3.8
Apr 27, 2019

1. What's the relationship between PCA and k-means clustering? 2. What are the requirements for a matrix to represent a kernel? What happens if we run SVM using a 'kernel' that does not satisfy these requirements? 3. Problems using Python lists and dictionaries 4. SQL joins, aggregates (count, sum, avg), and cases 5. If you were given a dataset with [X] features (may be numerical, categorial, etc.) and you want to build a model (to determine fraudulent transactions, say), how would you determine which features are best to use in the model?

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