​​Building Automated Feature Rollouts on Robust Regression Analysis

Nice article on important thing — statistical analysis of hypothesis testing. Every new feature or change made to existent one is basically an experiment. Article covers how #Uber team handles this in live system.

Link: https://eng.uber.com/autonomous-rollouts-regression-analysis/

#Uber #statistics #production #truestory

Battling Entropy: Making Order of the Chaos in Our Lives

Article on #entropy as a concept.

Link: https://fs.blog/2018/11/entropy/

A disciplined approach to neural network hyper-parameters

Recommendations on how to optimize learning rate, weight decay, momentum and batch size.

ArXiV: https://arxiv.org/pdf/1803.09820.pdf

#nn #hyperopt

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 café 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

​​Reproducibility tool for #Jupyter Notebooks

Link: https://mybinder.org

#DS #github #reproducibleresearch

​​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

Scikit-learn drops support of Python2.7 with new PR.

It means scikit-learn master now requires Python >= 3.5.

https://github.com/scikit-learn/scikit-learn/pull/12639

#scikitlearn

​​DeepTraffic — new RL competition hosted by #MIT

Link: https://selfdrivingcars.mit.edu/deeptraffic/
Github: https://github.com/lexfridman/deeptraffic

#RL #selfdrivingcar

A visual exploration of Gaussian Processes: beautiful interactive plots and a brief tutorial to make GPs more approachable

Link: https://www.jgoertler.com/visual-exploration-gaussian-processes/

#Statistics #GP #GaussianProcesses

Evaluating gambles using dynamics

Link: https://aip.scitation.org/doi/10.1063/1.4940236

#Statistics #Gambling