Friday Oct 25
15:45 –
16:30
B 09
Five Things I Learned while Prototyping ML Papers
As data scientists, building on published research allows us to stay on the cutting edge and not reinvent the wheel. However, in most cases, this transfer is not trivial. My talk will provide you with a five-step workflow that has made this transfer easier for me.
What will the audience learn from this talk?
How can we access the gold mine that is published research in ML, stats, and related fields, and turn it into nuggets and even refined gold jewelry useful for us? In other words, how we can evaluate the relevance, quality and reproducibility of research papers for our specific work situation.
Does it feature code examples and/or live coding?
No
Prerequisite attendee experience level:
Level 200
Keynotes
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Love Letter to the ComputerLinda LiukasThursday Oct 24 @ 09:15
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Composing Bach Chorales Using Deep LearningFeynman LiangThursday Oct 24 @ 13:15
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The Importance of LaughterAino Vonge CorryWednesday Oct 23 @ 09:15
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Interaction Protocols: It's All About Good MannersMartin ThompsonFriday Oct 25 @ 13:30
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Machine Learning: Alchemy for the Modern Computer ScientistErik MeijerWednesday Oct 23 @ 17:45
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Get Ready to Rock with Sonic Pi - The Live Coding Music Synth for EveryoneSam AaronThursday Oct 24 @ 17:45
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Welcome to a New Age of RefereeingPierluigi CollinaFriday Oct 25 @ 09:15
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Fueling the Quantum Application Era with the CloudMurray ThomFriday Oct 25 @ 17:40
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Extreme Digitalization in ChinaChristina BoutrupWednesday Oct 23 @ 13:15
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Special Appearance - Why Berlin?Aimée CovoFriday Oct 25 @ 16:45