This is a collection of resources for preparing for technical data science interviews. Material is grouped by topic, within each topic there is a collection of "Warm Up" questions, that cover basic definitions, theorems, and models. While presented as questions, these are more for practicing the basics that might get used in interview questions. For each technical interview section the questions are listed at the top as a table of contents with links to the answers down below.
The last section provides links to resources used in compiling this list of questions as well as additional resources that might be useful in preparing.
This website was created using Jupyter Book
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Have other good interview questions you want to add? Catch any typos or errors that need fixing? Everyone is welcome to contribute to this resource, my hope is that it can grow, and community contributions are the top way to making that happen. Use the Github links in the top right hand corner to suggest edits (via pull request) and/or create issues on the repository.