SF Bayarea Machine Learning meetup group
San Francisco Bay Area
Joined September 2012
- Tweets625
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- Followers17.9K
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SF Machine Learning retweeted
Early Bird is almost gone -- hurry up to get yours soon!
scale.bythebay.io/register
SF Machine Learning retweeted
And we are live!
Scale By the Bay 2020 program is live and registration is open!
Early bird through September 30.
Become a Patron By the Bay so we run the best online event this year and return by the bay next year.
Instantly sponsor with your logo.
scale.bythebay.io
SF Machine Learning retweeted
Sign up for #RaySummit—A FREE virtual event about Ray, the open-source Python framework for building distributed applications that run at any scale. You'll hear from experts such as @wesmckinn, founder of Ursa Labs and the creator of the pandas project. buff.ly/31ipI9J
SF Machine Learning retweeted
A couple of days left till Late Bird tickets go on sale. Do not miss out and book your ticket now. buff.ly/2NX42LG
SF Machine Learning retweeted
Excited to moderate the panel on AI Products with @AnimaAnandkumar @pbailis @tnguyenvnut at @scalebythebay 2019 sched.co/RtTU #scaleSF
SF Machine Learning retweeted
Highly recommend the excellent “Projects To Know” newsletter from @sarahcat21 & @AmplifyPartners: short, well-curated digests of interesting recent ML research papers, code repos, & blogs mailchi.mp/amplifypartners/p…
SF Machine Learning retweeted
We've revealed the speaker line-up! Join us at #ScaleByTheBay in San Francisco this November and hear from the top minds in functional programming, service architectures, data pipelines, and AI/ML at scale. scale.bythebay.io/speakers
SF Machine Learning retweeted
Determinant Point Processes are a simple way to model probabilities on subsets (combinatorial objects), e.g playlists, shopping baskets, Ad banners, etc. Here are 2 preprints on the subject:
(Non symmetric DPPs) arxiv.org/pdf/1905.12962.pdf
(Deep DPPs) arxiv.org/abs/1811.07245
Plse RT
SF Machine Learning retweeted
We are happy to announce the keynote speakers for SBTB 2019:
@helenaedelson
@jbeda
@heathercmiller
The CFP opens tomorrow and runs until May 31.
Submit your best talks early on
— functional programming
— service architectures
— data pipelines (including for ML/AI)
— &more!
SF Machine Learning retweeted
On #MastersOfData, @BenoitNewton chats with @sarahcat21, a Principal at @amplifypartners who focuses on startups that apply tech advances in machine intelligence & enterprise infrastructure to solve real-world problems. Listen in. bit.ly/2WcQA5P
SF Machine Learning retweeted
Personal news: Excited to announce that I've joined aifoundation.com to work on multimedia generation and detection problems. More details here:
deliprao.com/archives/331
SF Machine Learning retweeted
Prof. Rob Nowak (UWisc) had a saying (something like) "all of ML is just sophisticated smoothing" that had always stuck with me.
Enjoyed reading this OffConvex post on capabilities of modern GANs. Their conclusion, "GANs learn the distributions with low support" (which is just another way of saying they memorize training data well and produce outputs in a tiny neighborhood of that). offconvex.org/2017/07/06/GAN…
SF Machine Learning retweeted
Newly indexed videos have been linked in our our schedule. All videos from NeurIPS 2018 can be found here:
nips.cc/Conferences/2018/Vid…
SF Machine Learning retweeted
Videos from "Machine Learning for Programming" workshop ml4p.org/ are available at
youtube.com/playlist?list=PL…
SF Machine Learning retweeted
Syllabus & lecture slides for graduate-level probabilistic programming course from @frankdonaldwood at @UBC cs.ubc.ca/~fwood/CS532W-539W…
SF Machine Learning retweeted
This is a fantastic resource. It was written before the deep revolution and therefore provides good context for it all. I spent most of the the first year of my PhD jumping from chapter to chapter of this book.
"Pattern Recognition and Machine Learning" by @ChrisBishopMSFT is now available as a free download. Download your copy today for an introduction to the fields of pattern recognition & machine learning: aka.ms/prml #ML #Insights
SF Machine Learning retweeted
Brilliant list of actual AL/ML algorithms that "achieved" their "goals" by finding loopholes in the way the "goal" was specified by the programmers
Must read. Because this will happen increasingly often in the future—in increasingly critical areas
docs.google.com/spreadsheets…
SF Machine Learning retweeted
Slides posted - thanks everyone who attended, especially for interesting discussions & Qs! david-andrzejewski.com/publi…
.@davidandrzej of @SumoLogic shows absolutely mesmerizing type machinery to enforce privacy. HR dream!
SF Machine Learning retweeted
Java code decompiled from JVM bytecode autogenerated by Rainier for a compute graph with fixed observation data baked into the code itself for performance reasons 😲 - as explained by @avibryant (@stripe) at @ScaleByTheBay
SF Machine Learning retweeted
Can we do better than hand-annotating types into the comments of TF/PyTorch programs? @ctongfei (@JohnsHopkins PhD student) discussing typesafe deep learning @ScaleByTheBay GitHub.com/ctongfei/nexus
