Science News

http://www.admintome.com/blog/kafka-python-and-google-analytics/

https://neurosciencenews.com/learning-neurons-9516/

http://cs231n.github.io/understanding-cnn/

https://code.fb.com/data-infrastructure/spiral-self-tuning-services-via-real-time-machine-learning/

https://www.nist.gov/news-events/news/2018/06/nist-researchers-simulate-simple-logic-nanofluidic-computing

Oriented toward Clojure, but I think it doubles as a nice piece on different data structures & how to use them, and Doing Things with Functional Programming.  https://purelyfunctional.tv/guide/clojure-collections/

http://michaelfeathers.typepad.com/michael_feathers_blog/2011/05/the-carrying-cost-of-code-taking-lean-seriously.html

My friend gave this lecture!  https://www.youtube.com/watch?v=cx1l65kOtrg

https://theintercept.com/2018/06/25/att-internet-nsa-spy-hubs/

https://www.businessinsider.com/super-kamiokande-neutrino-detector-is-unbelievably-beautiful-2018-6

http://andrewgelman.com/2018/06/19/role-qualitative-methods-addressing-issues-replicability-reproducibility-rigor/

"Let me count the ways..." https://telescoper.wordpress.com/2018/06/19/why-the-universe-is-overrated/

https://blog.acolyer.org/2018/06/19/debugging-with-intelligence-via-probabilistic-inference/

http://www.r2d3.us/visual-intro-to-machine-learning-part-2/

https://machinelearningmastery.com/statistical-significance-tests-for-comparing-machine-learning-algorithms/

https://ai.googleblog.com/2018/04/announcing-open-images-v4-and-eccv-2018.html

https://nuit-blanche.blogspot.com/2018/06/paris-machine-learning-9-season-5.html

https://simplystatistics.org/2018/06/15/people-vs-institutions-in-data-analysis/

https://www.quantamagazine.org/mathematician-carina-curto-thinks-like-a-physicist-to-solve-neuroscience-problems-20180619/

https://beta.observablehq.com/@mbostock/methods-of-comparison-compared

https://www.quantamagazine.org/brains-may-teeter-near-their-tipping-point-20180614/

https://github.com/o1lab/xmysql

https://golem.ph.utexas.edu/category/2018/04/dynamical_systems_and_their_st.html

Kickin' rad MOOC that I'm taking right now, from a kickin' rad organization that does kickin' rad research. https://www.complexityexplorer.org/courses/63-algorithmic-information-dynamics-a-computational-approach-to-causality-and-living-systems-from-networks-to-cells

http://highscalability.com/blog/2018/6/18/how-ably-efficiently-implemented-consistent-hashing.html

I love it when you call me Big Data

http://blog.adnansiddiqi.me/getting-started-with-apache-kafka-in-python/

https://towardsdatascience.com/python-sets-and-set-theory-2ace093d1607

More useful than it sounds.

http://blog.lerner.co.il/python-parentheses-primer/

https://machinelearningmastery.com/statistical-sampling-and-resampling/

http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005268
Related: https://arxiv.org/abs/1806.04793

https://towardsdatascience.com/must-know-information-theory-concepts-in-deep-learning-ai-e54a5da9769d

https://www.math.toronto.edu/mathnet/questionCorner/geomean.html

http://www.electronicdesign.com/industrial-automation/more-details-emerge-about-arm-s-machine-learning

https://www.quantamagazine.org/evidence-found-for-a-new-fundamental-particle-20180601/