• Ken Jee

The Plagiarism Problem in Data Science


In this video I talk about my experience having my work plagiarized and about the broader plagiarism problem in data science. I hope to help cut through the ambiguity associated with plagiarism in data science by clearly defining it, talking about how you can avoid it in your data science projects, and about some of the negative consequences associated with it.


This is a cautionary tale. Plagiarism can have disastrous consequences, like for my fellow youtuber Siraj Raval. I hope that we can learn from others mistakes and avoid this type of behavior in the future.

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