How to write a good machine learning tutorial. https://t.co/YWTtQjCEpr pic.twitter.com/0bwccXZz0w
— hardmaru (@hardmaru) March 30, 2019
How to write a good machine learning tutorial. https://t.co/YWTtQjCEpr pic.twitter.com/0bwccXZz0w
— hardmaru (@hardmaru) March 30, 2019
The 996 work schedule is inhumane. https://t.co/ajXt3YKRAc
— Guido van Rossum (@gvanrossum) March 29, 2019
This has been the most popular slide from my first talk about Becoming a Data Scientist!
— Data Science Renee (@BecomingDataSci) March 29, 2019
Full talk here:https://t.co/zLrkqTGijf https://t.co/2HQy8zOG0I
When you’re A/B testing, you should not just be guessing and trying random things. Be hypothesis-driven: what user problem are you trying to solve, why would this work, and how will you measure success? @lukasvermeer #cxllive pic.twitter.com/pQ7J2ymdqF
— Emily Robinson (@robinson_es) March 28, 2019
People who think the Apple Card is the beginning of Apple or Amazon's entry into retail banking do not know enough about banking regulation and its ban on commercial entities providing banking services (I know enough to know that much) https://t.co/Ej1TeEuxkI
— Tim Wu (@superwuster) March 28, 2019
Important advice for AI researchers & devs:
— Rachel Thomas (@math_rachel) March 27, 2019
- privilege domain expertise
- include communities that will be impacted at every step (& pay them for their expertise)
- embrace what we don't know & have humility
- advocate for diverse voices@DrDesmondPattonhttps://t.co/clQVmhJS4D pic.twitter.com/M3x0YEIZv7
Great thread on one example of how “correlation vs causation” manifests in the wild.
— Angela Bassa (@AngeBassa) March 27, 2019
Egg eating 🍳 is likely not *per se* good or bad for you, at least not enough to clinically matter—but it’s likely a marker for all sorts of other potentially causal links. https://t.co/5cUyNLR98Y
At some pt some policy genius is going to realise that the reason so many academics burn out & underachieve is b/c of unrelenting pressure to achieve stratospheric “excellence” at all times w/ everything continually assessed thru peer review, PDRs, REF, TEF, progress reports etc. https://t.co/NtWY096yBc
— Chris Chambers (@chrisdc77) March 27, 2019
Sometimes validation loss < training loss. Ever wondered why? 1/5 pic.twitter.com/2FOKQ1kY0w
— Aurélien Geron (@aureliengeron) March 27, 2019
"Data is fundamentally about power." @CJPiovesan #StrataData pic.twitter.com/L0TIUJbTfj
— Rachel Thomas (@math_rachel) March 26, 2019
Robotics at @GoogleAI is making great progress in using machine learning to get robots to start doing practical things, from navigating rooms to handling everyday objects, in a way that works well alongside people. Today's NYTimes has a good overview:https://t.co/pNSxLp1Zlj
— Jeff Dean (@JeffDean) March 26, 2019
The inaugural AI2 Newsletter | March 2019: https://t.co/ke2XVfUsCQ
— Oren Etzioni (@etzioni) March 26, 2019
Concise, accessible, and informative about our latest work. Please spread the word.