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	Podcast:		Talk Python To Me - Python conversations for passionate developers
	Episode:		#252 What scientific computing can learn from CS
	Category:		Technology
	Duration:		01:10:58
	Publish Date:		2020-02-21 00:00:00
	Description:		Did you come into Python from a computational science side of things? Were you just looking for something better than Excel or Matlab and got pulled in by all the Python has to offer? That's great! But following that path often means some of the more formal practices from software development weren't part of the journey. On this episode, you'll meet Martin Héroux, who does data science in the context of academic research. He's here to share his best practices and lessons for data scientists of all sorts. Links from the show Neuroscience Research Australia: neura.edu.au Martin Héroux: researchgate.net Errors in science: I make them do you? Part 3: scientificallysound.org PyPI Packages DABEST: pypi.org/project/dabest PSYCHOPY: pypi.org/project/PsychoPy Spreadsheet Blunders 12 of the Biggest Spreadsheet Fails: blogs.oracle.com Common spreadsheet errors: datacarpentry.org Best Practices for Scientific Computing: journals.plos.org Good enough practices in scientific computing: journals.plos.org Full episode RSS feed: talkpython.fm/episodes/rss_full_history Springboard bootcamp scholarships [code TALKPYTHONTOME]: talkpython.fm/springboard Sponsors Clubhouse Linode Talk Python Training
	Total Play:		0