Data Mishaps Night is a night where we embrace the messiness of data work. Whether you're a seasoned data practitioner or just starting out, there's something for everyone.
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Data Mishaps Night is a night where we embrace the messiness of data work. Whether you're a seasoned data practitioner or just starting out, there's something for everyone.
Exploring the new AI term LAMs (Large Action Models). What it means and how it relates to LLMs and AI agents.
How making and sharing mistakes can supercharge your growth
How to navigate your career when your compass feels broken
“Machine Learning for Kids” is a website that educates children on the subject of Machine learning through hands on play.
#BlackInDataWeek is a free, online data conference taking place November 16-21, 2020
It's a week-long celebration to (1) highlight the valuable work and experiences of Black people in the field of Data, (2) provide community, and (3) educational and professional resources.
Sharing some of my favorite data science and data foundation books for young kids!
A step by step approach to breaking down your business problem into a less intimidating data problem.
Check out the Data.gov website to discover a treasure trove of datasets made publicly available by the governments.
Tips and tricks to creating easy to follow technical tutorials.
Aiming to ease your RStudio::Conf FOMO by sharing as much R and conference information as possible. The goal is to help everyone feel included, ready to level up their R skills and engage with the community!
I’m taking data democracy on the road with podcasts and conference talks!
An overview of my experience in the NASA Datanaut kickoff session
Lower the barriers to productivity by employing a “Select your own adventure” approach to on-boarding your new analytics team members.
As predictive analytics takes one step closer to mainstream adoption, we explore the concept in detail and break it down into actionable steps.
A blog exploring the promise vs reality of NPS, alternatives and how to use the metric responsibly.
A business case for adopting the minimum viable product approach to analytics.