Data Science by ODS.ai 🦜
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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @haarrp
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​​The new ResNet PoseNet model is much more accurate than the MobileNet one (the trade off being size & speed). The model is quantized & 25MB.
Pose estimation model, capable of running on devices

This model is really great for art installations or running on desktops.

Demo (requires camera, will work on desktop): https://storage.googleapis.com/tfjs-models/demos/posenet/camera.html?linkId=69346544
Github: https://github.com/tensorflow/tfjs-models/tree/master/posenet

#tensorflow #tensorflowjs #js #pose #poseestimation #posenet #ResNet #device #ondevice
Estimating the success of re-identifications in incomplete datasets using generative models

99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes, suggesting that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization set forth by GDPR.

This is a big concern about privacy and a problem for Data Engineering, especially for those working with anonymized personal information. Paper provides a way to re-identify person from anonymized dataset, this can be useful for people who work for government or security companies

https://www.reddit.com/r/science/comments/chko43/9998_of_americans_would_be_correctly_reidentified/

#privacy #gdpr #federatedlearning #ml
​​Baidu’s Optimized ERNIE Achieves State-of-the-Art Results in Natural Language Processing Tasks

#Baide developed ERNIE 2.0, a continual pre-training framework for language understanding. The model built on this framework has outperformed #BERT and #XLNet on 16 tasks in Chinese and English.

Link: http://research.baidu.com/Blog/index-view?id=121

#NLP #NLU
​​🔥Interactive demo of GAN turning doodles into beautiful pictures

NVidia released #GauGAN for anyone to use. Trained on 1M images, the #GAN tool automatically turns doodles into photorealistic landscapes.

Project page: https://www.nvidia.com/en-us/research/ai-playground/
Interactive demo: http://nvidia-research-mingyuliu.com/gaugan

#Nvidia #CV #DL
21k followers — best feedback from the audience!

Thank you!
ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.
​​New paper on training with pseudo-labels for semantic segmentation

Semi-Supervised Segmentation of Salt Bodies in Seismic Images:
SOTA (1st place) at TGS Salt Identification Challenge.

Github: https://github.com/ybabakhin/kaggle_salt_bes_phalanx
ArXiV: https://arxiv.org/abs/1904.04445

#GCPR2019 #Segmentation #CV
​​Long-form question answering

Facebook AI shared the first large-scale data set, code, and baseline models for long-form QA, which requires machines to provide long, complex answers — something that existing algorithms have not been challenged to do before.

Link: https://ai.facebook.com/blog/longform-qa/

#FacebookAI #Facebook #NLP #NLU #QA
ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.
Data Science by ODS.ai 🦜
ODS breakfast in Paris! See you this Saturday at 10:30 at Malongo Café, 50 Rue Saint-André des Arts.
You do not need any presentation or preparation, this is free format for people who are around these days and wanna chat with fellow data scientists
​​Photo to anime portrait

U-GAT-IT — Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation.

Link: https://github.com/taki0112/UGATIT

#Tensorflow #GAN #CV #DL #anime
​​Unified rational protein engineering with sequence-only deep representation learning

UniRep predicts amino-acid sequences that form stable bonds. In industry, that’s vital for determining the production yields, reaction rates, and shelf life of protein-based products.

Link: https://www.biorxiv.org/content/10.1101/589333v1.full

#biolearning #rnn #Harvard #sequence #protein
A Guide for Making Black Box Models Explainable.

One of the biggest challenges is to make ML models interpretable (explainable to human, preferably, non-expert). It matters not only in terms of credit scoring, to exclude possibility of racism or any other bias or news promotion and display (Cambridge Analytica case), but even in terms of debug and further progress in model training.


Link: https://christophm.github.io/interpretable-ml-book/

#guide #interpretablelearning #IL
​​Simple real time visualisation of the execution of a #python program: https://github.com/alexmojaki/heartrate
Forwarded from Karim Iskakov - канал (Vladimir Ivashkin)
T-shirt to inject junk data into surveillance systems. Stylish tool for peaceful protest against state human tracking
🔎 adversarialfashion.com
📉 @loss_function_porn