Evaluating gambles using dynamics

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

#Statistics #Gambling

​​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

How I used NLP (Spacy) to screen Data Science Resumes

Example on how #notAIyet can be used to ease day-to-day job.

Link: https://towardsdatascience.com/do-the-keywords-in-your-resume-aptly-represent-what-type-of-data-scientist-you-are-59134105ba0d

#NLP #HR #DL

AutoML: Automating the design of machine learning models for autonomous driving

Link: https://medium.com/waymo/automl-automating-the-design-of-machine-learning-models-for-autonomous-driving-141a5583ec2a

#Waymo #automl #DL #selfdriving #Google

Valuing Life as an Asset, as a Statistic and at Gunpoint

Ever wondered, how much your life is worth? This is an article about Life as an asset evaluation. It is extremely useful for insuarance companies and as a metric to calculate compensations in case of tragic events, but it is also a key to understand, how valuable (or not) life is.

Math is beautiful.

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3156911

#math #life #insurance #statistics

Learning from Dialogue after Deployment: Feed Yourself, Chatbot!

From abstract: The self-feeding chatbot, a dialogue agent with the ability to extract new training examples from the conversations it participates in.

This is an article about chatbot which is capable of true online learning. There is also a venturebeat article on the subject, covering the perspective: «Facebook and Stanford researchers design a chatbot that learns from its mistakes».


Venturebeat: https://venturebeat.com/2019/01/17/facebook-and-stanford-researchers-design-a-chatbot-that-learns-from-its-mistakes/
ArXiV: https://arxiv.org/abs/1901.05415

#NLP #chatbot #facebook #Stanford

🤓Interesting note on weight decay vs L2 regularization

In short, the was difference when moving from caffe (which implements weight decay) to keras (which implements L2). That led to different results on the same net architecture and same set of hyperparameters.

Link: https://bbabenko.github.io/weight-decay/

#DL #nn #hyperopt #hyperparams

​​IQ is largely a pseudoscientific swindle

Note by Nassim Taleb on how IQ works. He shows that high-IQ is not well-correlated with wealth or overall cognitive performance.

Link: https://medium.com/incerto/iq-is-largely-a-pseudoscientific-swindle-f131c101ba39

#statistics #iq #fallacy

Implementing a ResNet model from scratch.

Well-written and explained note on how to build and train a ResNet model from ground zero.

Link: https://towardsdatascience.com/implementing-a-resnet-model-from-scratch-971be7193718

#ResNet #DL #CV #nn #tutorial

Understanding Convolutional Neural Networks through Visualizations in PyTorch

Explanation of how #CNN works

Link: https://towardsdatascience.com/understanding-convolutional-neural-networks-through-visualizations-in-pytorch-b5444de08b91

#PyTorch #nn #DL

​​Object detection SOTA evolution over time.

#SOTA #CNN #objectdetection

Deep learning for NLP crash course at ABBYY.

Github repo with scheduled plan for learning #DL #NLP online.

Link: https://github.com/DanAnastasyev/DeepNLP-Course

#educational #tutorial #course #beginner #novice #entrylevel

Mastermind: Using Uber Engineering to Combat Fraud in Real Time

Article on general aspects of how #Uber’s fraud prevention engine works.

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

#architecture

News Feature: What are the limits of deep learning?

Nice article summarizing recent progress in deep learning. It can be renamed into «Recent progress in deep learning leaves DL critics searching for new things to criticize».

Link: https://www.pnas.org/content/116/4/1074

#DL #Meta

#DeepMind will show AI playing #Starcraft II.

Starts in 8 hours (6:00 PM GMT)

youtube.com/c/deepmind / https://www.twitch.tv/starcraft

#RL

Upcoming series of #ML lectures from Columbia Universite will be published on youtube.

If you are looking #wheretostart, this is one of the great places.

YouTuve Playlist: https://www.youtube.com/playlist?list=PL_pVmAaAnxIQGzQS2oI3OWEPT-dpmwTfA
Syllabus: https://www.cs.columbia.edu/~amueller/comsw4995s19/schedule/

#beginner #novice #entrylevel

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