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: @malev
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Free online ODS.AI course on ML

Another great free course will start on February 11. Taught through #Kaggle notebooks and competitions.

Link: https://www.kaggle.com/general/77771

#entrylevel #novice #beginner
There is another Data Science Breakfast at Paris upcoming on this Saturday at 10:00 AM at Strada Cafe, 24 Rue Monge.

Feel free to join, regardless of your level. Everyone is welcome.
Discovering and Classifying In-app Message Intent at Airbnb

An article on how #AirBnB finds intent in conversations to make its service better.

Link: https://medium.com/airbnb-engineering/discovering-and-classifying-in-app-message-intent-at-airbnb-6a55f5400a0c

#NLP #intent
Natural Questions

Google published Natural Questions, a new, large-scale corpus and challenge for training and evaluating open-domain question answering systems, and the first to replicate the end-to-end process in which people find answers to questions.

Link: https://ai.googleblog.com/2019/01/natural-questions-new-corpus-and.html

#Google #NLP #data
Dynamic Transfer Learning for Named Entity Recognition

Paper with direct healthcare application by #Amazon interesting proposal to use Dynamic Transfer Network for architecture search

Link: https://arxiv.org/pdf/1812.05288.pdf

#healthcare #NLP
VeGAN release

A small library to easily train various existing #GAN using #PyTorch. Based on provided generator and discriminator, VeGANs trains them with a selected GAN algorithm.

Link: https://github.com/unit8co/vegans
StanfordNLP release.

New Python #NLProc package. StanfordNLP provides native, neural (PyTorch) tokenization, POS tagging and dependency parsing for 53 languages based on UD v2 β€” and a Python CoreNLP interface.

Pip: pip install stanfordnlp
PyPI: https://pypi.org/project/stanfordnlp/
Link: https://stanfordnlp.github.io/stanfordnlp/

#NLP #Stanford
Forwarded from Just links
Typical data scientist/machine learning engineer:
> understands that data science is generally engineering most of programmers can deal with
> do want to be overpaid and thus to keep others away from field
> keeps saying rare useless skill he possesses is definitively necessary for data science
Towards reconstructing intelligible speech from the human auditory cortex



Columbia neuroengineers have created a system that translates thought into intelligible, recognizable speech. By monitoring someone's brain activity, the technology can reconstruct the words a person hears with unprecedented clarity.

Link: https://www.nature.com/articles/s41598-018-37359-z

#BCI #thought2text
​​StNet: Local and Global Spatial-Temporal Modeling for Action Recognition

Baidu in one of #AAAI19 papers, proposed StNet, a novel framework for both local and global spatial-temporal modeling in videos. StNet outperforms several state-of-the-art approaches in action recognition and balances btw accuracy and model complexity.

ArXiV: https://arxiv.org/pdf/1811.01549.pdf

#SOTA #Baidu
​​DeepSlide: A Sliding Window Framework for Classification of High Resolution Microscopy Images (Whole-Slide Images)

DeepSlide, our #DeepLearning library for classification/visualization of high-resolution pathology images is open-source and available on GitHub.

GitHub: https://github.com/BMIRDS/deepslide

#histopathology #healthcare #PyTorch
​​Introducing AresDB: Uber’s GPU-Powered Open Source, Real-time Analytics Engine

Link: https://eng.uber.com/aresdb/

#Uber #analytics #opensource
​​Fair Regression for Health Care Spending

What happens, if fairness built into the objective function for continuous outcomes & see large improvements in group undercompensation?

This is the most interesting & potentially impactful analysis of fairness in #ML for #healthcare, which can lead to significant improvement in the life of millions.

ArXiV: https://arxiv.org/abs/1901.10566
GitHub: https://github.com/zinka88/Fair-Regression

#statistics #regression
​​Bayesian Statistics explained to Beginners in Simple English

Now some #entrylevel material, which still might be useful to review, because repetitio est mater studiorum.

Link: https://www.analyticsvidhya.com/blog/2016/06/bayesian-statistics-beginners-simple-english/