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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Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

List mostly for beginners.

Link: https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html

#novice #beginner #ipython #jupyter
Tomorrow (05 Jan) we are holding first offline meeting for this channel members and all the Data Scientists in Paris.

You are kindly welcome to come by Malongo cafΓ© at 10:00 to chat, share experience and have a coffee with fellow data scientist if you are in Paris these days.
Rachael’s #cheatsheet on choosing #DS library.
A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain

Computer Vision can detect Alzheimer’s Disease in brain scans SIX YEARS before a diagnosis. Uses PET scans, which are common & cheaper. 82% specificity at 100% sensitivity. Can pick out signs hard to see with the naked eye.

Link: https://pubs.rsna.org/doi/10.1148/radiol.2018180958

#CV #DL #Alzheimer #medical
​​Automatically Generating Comments for Arbitrary Source Code

Automatically generating code comments directly from source code using an LSTM. Works with multiple languages. Can’t wait to JetBrains discovering it.

Link: https://www.twosixlabs.com/automatically-generating-comments-for-arbitrary-source-code/

#NLP #CS #coding #LSTM
Data Science Breakfast in Paris. Thanks again for coming, hopefully this will setup a regular DS Breakfast in Paris.
​​Generalization in Deep Networks: The Role of Distance from Initialization

Why it's important to take into account the initialization to explain generalization.

ArXiV: https://arxiv.org/abs/1901.01672

#DL #NN
​​POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer

POET: it generates its own increasingly complex, diverse training environments & solves them. It automatically creates a learning curricula & training data, & potentially innovates endlessly.

Link: https://eng.uber.com/poet-open-ended-deep-learning/

#RL #Uber
​​Super-resolution GANs for improving the texture resolution of old games.

It is what it is. #GAN to enhance textures in old games making them look better.

ArXiV: https://arxiv.org/abs/1809.00219
Link: https://www.gamespot.com/forums/pc-mac-linux-society-1000004/esrgan-is-pretty-damn-amazing-trying-max-payne-wit-33449670/

#gaming #superresolution
​​How Uber predicts prices

Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

Link: https://eng.uber.com/neural-networks-uncertainty-estimation/

#RNN #LSTM #Uber
Plug-and-play differential privacy for your tensorflow code

#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.

where you would write tf.train.GradientDescentOptimizer
instead just swap in the DPGradientDescentOptimizer


Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy

#Privacy #tensorflow
​​Desnapify

Logical followup of #pix2pix project by Isola et al., based on on Keras implementation by Thibault de Boissiere allows to remove that kat/dog faces from #Snapchat photoes.


Github: https://github.com/ipsingh06/ml-desnapify
Mentioned #Keras repo: https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/pix2pix

#DL