@JupyterCon starts next Wednesday! And did you know you can get single-day passes to the conference at a lower rate? 🙌🤸
Get your tickets now & don't let this fantastic conference pass you by: https://t.co/KPPsB0hi5y! #opensource#jupyter#techconferences#scientificcomputing
Saluting Distinguished Teaching Career: Faculty & staff colleagues honor electrical & computer eng. professor Cliff Grigg after teaching his last class before retirement this fall. This is his 37th year on #rosehulman faculty. He earned the 2021 Dean's Outstanding Teacher Award.
really excited for @PyData Global next week! Really impressed by the quality of the content at PyData Miami a couple of years ago, given it was the first time they'd had a local conference. I can only imagine this virtual conference is going to be even better!
Strava's data team is hiring for a lot of roles right now! We're looking for full-time analysts and data engineers at multiple seniorities and also for our next class of analytics interns! Please apply or refer someone! #datascience#fittech#analytics
https://t.co/vib4GPVWlP
Strava's data team is hiring for a lot of roles right now! We're looking for full-time analysts and data engineers at multiple seniorities and also for our next class of analytics interns! Please apply or refer someone! #datascience#fittech#analytics
https://t.co/vib4GPVWlP
Strava's data team is hiring for a lot of roles right now! We're looking for full-time analysts and data engineers at multiple seniorities and also for our next class of analytics interns! Please apply or refer someone! #datascience#fittech#analytics
https://t.co/vib4GPVWlP
I'm doing a giveaway of my book, Hiring Data Scientists and Machine Learning Engineers 🥳🤑📚
https://t.co/qEoLjdWTfr
♻️Retweet this and I'll randomly choose a winner next Tues, 19 Oct, from those who retweet♻️
If this gets more than 100 retweets I'll select two winners 🚀🚀🚀
This whole thread, but especially this point I think is so great. Data doesn't just exist- it is produced- and to understand how it's produced is to understand the assumptions baked into the data
Machine learning focuses a lot on the parts of statistics that can be automated and it's hard to automate a deep sociological understanding of race and gender and the cultural processes that cause bias in the production data. 8/9
My personal favorite example/pet peeve is "variance"
In statistics: the spread of a distribution about a sample/distribution mean
In finance/MBA parlance: the difference between an actual/realized value and a forecasted/projected one
One of the hardest parts of science communication is talking with scientists in other fields & it’s mostly because of what I like to call: “jargon homonyms”
These are words which look & sound the same, & have very specific technical meanings—but the meanings are *field-specific*