The expression “garbage in, garbage out” is known to all. But what does this mean for machine learning and data mining? This talk will explore several case where application of machine learning approaches have failed (or misled the practitioners with erroneous success) because of deficiencies in training data, poor documentation of feature sets, violation of tacet mathematical assumptions, or naive application of techniques.
Bio:
Jeff Chen is Deputy Chief Data Officer of the US Department of Commerce where he leads the Commerce Data Service working to integrate data science into policy and operations. A statistician by trade, he has led and deployed data-driven efforts in 35 fields in a dozen countries as well as has led and contributed to efforts at NASA, the White House Office of Science and Technology Policy, the NYC Fire Department, the Clinton Health Access Initiative, and the NYC Mayor’s Office.
by Katie Mead (’24)
Journey to Georgetown
My journey to data science started during the Covid-19 pandemic. I had moved from Virginia to Nashville, TN for Teach For America. My placement was in…
Participating in a Hackathon is an important milestone in any data scientist’s journey. Hackathons provide an exciting opportunity to take the skills and techniques you’ve learned and apply them to solving a challenging business problem for a company.…
The first two days of December saw DSAN partnering with Lander Analytics to host the R Gov Conference. The R Gov Conference hosts one of the most elite gatherings of data scientists and data professionals who come together to explore, share, and inspire ideas, and to promote the growth of open-source ideals.…
On Saturday, October 22, we partnered with DataKindDC for an all-day data dive, giving our students a chance to work in real-time alongside local volunteer data scientists on projects for four non-profits to move the selected organization’s programming forward and benefit the communities they serve.…