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Data Science Glossary No ratings yet.

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Created/Published/Taught by:
Bob DuCharme

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Bob DuCharme

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from datascienceglossary About page:

“Terms included in this glossary are the kind that typically come up in data science discussions and job postings. Most are from the worlds of statistics, machine learning, and software development.

Bob DuCharme is the author of O’Reilly’s Learning SPARQL and several other books, as well as a solution architect for TopQuadrant, the leading provider of software and solutions for modeling, developing and deploying semantic web applications.”

from the author’s blog:

“Lately I’ve been studying up on the math and technology associated with data science because there are so many interesting things going on. Despite taking many notes, I found myself learning certain important terms, seeing them again later, and then thinking “What was that again? P-values? Huh?”

So, I turned a portion of my notes into a glossary to make these things easy to look up when I wanted to remember them. I decided that I may as well publish this glossary in case others found it helpful, or if they had suggestions or corrections. And, when I found that the domain name datascienceglossary.org wasn’t taken, I couldn’t resist grabbing it.

I hope my data science glossary is useful to some people. I know it will be useful to me, especially the next time I forget what “P-value” means.”

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