AI, Python, Cognitive Neuroscience
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[MobiNetV1] Removing people from complex backgrounds in real time using TensorFlow.js in the web browser!

This code attempts to learn over time the makeup of the background of a video such that the algorithm can attempt to remove any humans from the scene. This is all happening in real time, in the browser, using TensorFlow.js.


https://lnkd.in/gsePqBH

#deeplearning #machinelearning #artificialintelligence

❇️ @AI_Python_EN
PyTorch Implementation and Explanation of Graph Representation Learning papers involving DeepWalk, GCN, GraphSAGE, ChebNet & GAT.


https://github.com/dsgiitr/graph_nets

❇️ @AI_Python_EN
jeremy howardWe're launching fastpages, a platform which allows you to host a blog for free, with no ads. You can blog with ProjectJupyter
notebooks, office
Word, directly from github
's markdown editor, etc.

Nothing to install, & setup is automated!

https://fastpages.fast.ai/fastpages/jupyter/2020/02/21/introducing-fastpages.html

❇️ @AI_Python_EN
Localized Narratives multi-modal annotations released!
White heavy check mark 628k images, White heavy check mark 6400 km of mouse traces,White heavy check mark 1.5 years of voice recordings,White heavy check mark
650k captions.All synchronized.
https://google.github.io/localized-narratives/

❇️ @AI_Python_EN
When ML models are deployed, data distributions evolving over time leads to a drop in performance. Our latest paper (theory and experiments) suggests we can use self-training on unlabeled data to maintain high performance
https://arxiv.org/pdf/2002.11361.pdf

❇️ @AI_Python_EN
Covid-19, your community, and you — a data science perspective

https://www.fast.ai/2020/03/09/coronavirus/

❇️ @AI_Python_EN
Here's an update from Dan Jurafsky and the #acl2020nlp team re COVID19:

https://acl2020.org

#NLProc
Can a shiny app be a paper? Heck yeah!
Red question mark ornament
"Where to publish your Shiny App?"

https://buff.ly/3cOqSNU #rstats #rshiny
We have just released Multi-SimLex v1: a new multilingual #NLProc resource for semantic similarity. It covers 1,888 concept pairs across 12 typologically diverse langs, plus 66 xling data sets. .

https://multisimlex.com

Multi-SimLex provides a new, typologically diverse evaluation benchmark for representation learning models. See our paper for experiments and interesting analysis:

https://arxiv.org/pdf/2003.04866.pdf

But this is not all! We are also launching a collaborative initiative to extend Multi-SimLex to cover many more of the world’s languages! Please join us in this effort to create an extensive semantic similarity resource for the needs of contemporary multilingual #NLProc.We welcome your contributions for both small and major languages! Follow the guidelines at https://multisimlex.com to create and submit a Multi-Simlex -style dataset for your favourite language. All the
contributions will be shared with everyone via the Multi-SimLex site.
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Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner.

abs: https://arxiv.org/abs/2002.05534v1

#rnn #machinelearning #ArtificialIntelligence #DeepLearning #

❇️ @AI_Python_EN
A PyTorch re-implementation of Generative Teaching Networks has been made available by GoodAIdev https://lnkd.in/giJBSw3 Nice to see! https://lnkd.in/gzGMJBn
Access 2 new free online courses
as of today on edXOnline
It's time to hone your #digitalintelligence knowledge and skills, even more if you're getting bored at home:
http://bit.ly/2WLF58R

#DeepLearning

❇️ @AI_Python_EN
Help us scale #COVID19 detection over the phone.

If you have a #COVID19 diagnosis or are healthy, consider recording a breathing sample anonymously at https://breatheforscience.com

We hope this data leads to techniques to help diagnosis of #COVID19 over the phone.

❇️ @AI_Python_EN