It's extremely important that we anticipate & critically examine the harms of false positives in algorithmic decision-making. Not only in practice (like this real world scenario!) but in scholarship--if you classify things, let's see discussion of what happens when you're wrong. https://t.co/yhm0gBuVjz
— Casey Fiesler (@cfiesler) July 8, 2018
probably shouldn't share it publicly, but I have too many projects to work on at the moment anyway: had a great idea to improve ELMs further, ie dropping the hidden layer(s) + run n ELMs with n different random seeds to construct a majority vote ensemble. Someone should try this!
— Sebastian Raschka (@rasbt) July 8, 2018
Why Sci-Hub is illegal, and what you can do about it https://t.co/ng4N791SzH pic.twitter.com/IcsfFavBfS
— Sci Hub (@Sci_Hub) July 7, 2018
How did I only just find out about this package??? https://t.co/aXJe2zLRC3. You have all let me down!
— Hadley Wickham (@hadleywickham) July 6, 2018
A summary of AI strategies adopted by various countries.https://t.co/s7RULVCRnN https://t.co/s7RULVCRnN
— Yann LeCun (@ylecun) July 6, 2018
Our CTO @Kevin_Scott joined @ThinkMariya of TOPBOTS to discuss the opportunities #AI and #IoT present for our future: https://t.co/nquDVkhtRy https://t.co/TPAOJe5N8s
— Microsoft (@Microsoft) July 6, 2018
Plotly's new #Python interface: fast rendering of huge datasets, interactive #Jupyter notebooks, validation… This is huge! https://t.co/iRzERrUdQX by @jonmmease 👍 pic.twitter.com/VvnGdmgGEk
— Radim Řehůřek (@RadimRehurek) July 6, 2018
That $35 that scientific journals charge you to read a paper goes 100% to the publisher, 0% to the authors. If you just email us to ask for our papers, we are allowed to send them to you for free, and we will be genuinely delighted to do so. https://t.co/NHEfiOMLfG
— Dr. Holly Witteman (@hwitteman) July 6, 2018
A useful paradox for data scientists to keep in mind:
— David Robinson (@drob) July 5, 2018
Most cities are small, but most people live in large cities
This relates to analyses of e.g. user engagement: most of your users probably don't do much, but most of your engagement is from frequent users
An astonishing paper that may explain why it’s so difficult to patch.
— Gene Kim (@RealGeneKim) July 5, 2018
They monitored 400 libraries. In 116 days, they saw 282 breaking changes!
Each day, there’s 6.1% chance of breaking chg, for each lib you use!@topopal @mtnygard @mik_kersten @ctxthttps://t.co/qdRswgAwm2 pic.twitter.com/sns2IOoK0L
This 1795 essay by Laplace is fun to read: https://t.co/AsuW3ngw9h
— Ian Goodfellow (@goodfellow_ian) July 5, 2018
I think of the reasons spreadsheet software is more approcahable than R/Python for a lot of folks is that you can directly see & manipulate the data structure. Learning how to conceptualize data structures is a specialized skill that takes time to learn.
— Rachael Tatman (@rctatman) July 5, 2018
