It is proven! I am burakince on Keybase: https://keybase.io/burakince/sigchain#e972ed8f02e0052f162cd5ee929ae7071654baeb513d79f752c0dacbc25206680f
"Practical Guide to Controlled Experiments on the Web: Listen to Your Customers not to the HiPPO" by Ron Kohavi, Randal M. Henne, Dan Sommerfield https://ai.stanford.edu/~ronnyk/2007GuideControlledExperiments.pdf
A real-world example of a prediction problem in the health/medical sciences domain - training a classifier to predict the risk of autism spectrum disorder (ASD) based on genetic markers. https://www.the-scientist.com/news-opinion/genetic-test-for-autism-refuted-38511
A Few Useful Things to Know about Machine Learning by Prof. Pedro Domingos https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP lectures. https://github.com/kmario23/deep-learning-drizzle
@judeswae Actually I don't have information yet. I guess, last five days somehow it was a hot topic in Turkey.
Cirq, an open-source quantum framework for building and experimenting with noisy intermediate scale quantum (NISQ) algorithms on near-term quantum processors. https://ai.googleblog.com/2018/07/announcing-cirq-open-source-framework.html
Why and how automated processes for decision-making, particularly applications of machine learning, can exhibit bias in subtle and not-so-subtle ways http://approximatelycorrect.com/2016/11/07/the-foundations-of-algorithmic-bias/
Eheheh :) You can submit your name from here -> https://mars.nasa.gov/participate/send-your-name/mars2020/
Hyperdimensional computing theory could lead to AI with memories and reflexes https://thenextweb.com/artificial-intelligence/2019/05/17/hyperdimensional-computing-theory-could-lead-to-ai-with-memories-and-reflexes/
Billion-scale semi-supervised learning for image classification https://arxiv.org/abs/1905.00546
Ten Simple Rules for Better Figures https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833
papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. https://github.com/nteract/papermill
Notebook Usages at Netflix
Part 1: Notebook Innovation at Netflix https://medium.com/netflix-techblog/notebook-innovation-591ee3221233
Part 2: Scheduling Notebooks at Netflix https://medium.com/netflix-techblog/scheduling-notebooks-348e6c14cfd6
Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts by Scott Bateman, Regan L. Mandryk, Carl Gutwin, Aaron Genest, David McDine and, Christopher Brooks http://hci.usask.ca/uploads/173-pap0297-bateman.pdf
Harness raises $60 million to automate continuous app delivery with machine learning https://venturebeat.com/2019/04/23/harness-raises-60-million-to-automate-continuous-app-delivery-with-machine-learning/
Reflections on the Challenges and Pitfalls of Evidence-Driven Visual Communication by Alberto Cairo https://infovis.fh-potsdam.de/readings/Cairo2015.pdf #datascience
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