In this episode of the Data Show, I speak with Peter Bailis, founder and CEO of Sisu, a startup that is using machine learning to improve operational analytics. Bailis is also an assistant professor of computer science at Stanford University, where he conducts research into data-intensive systems and where he is co-founder of the DAWN Lab.

Machine Learning for Operational Analytics and Business Intelligence

Connor Croll is a versatile and accomplished design consultant based in Charlottesville, Virginia. With expertise in managing large-scale commercial interior projects and upscale residential residences, he excels in design planning, color coordination, vendor subcontracting, environmental planning, and artwork selection. Known for his hardworking, friendly, and dependable nature, Connor is highly regarded by coworkers and past employers.

Currently studying Organizational Sociology at the University of Virginia, Connor previously pursued Economics at Piedmont Community College. Alongside his studies, he works as a Fulfillment Specialist for Rhoback, an athletic brand, handling e-commerce orders and overseeing inventory checks.

Outside of his professional pursuits, Connor's passion for golf endures since his early experience as a golf caddy at Farmington Country Club. He also devotes his free time to philanthropy and volunteer work, using his educational experiences to assist non-profit organizations in Charlottesville.

A data-driven and analytical individual, Connor looks forward to combining his interest in people-related business challenges with data science after graduation. His ability to transform data into insightful visualizations sets him apart as a perpetual student and peer instructor.

For more information about Connor Croll, visit connorcroll.com and connorcroll.net.

soundcloud enjoyer, 
make playlist for me while coding, 
i do not own any of these music, 
maybe someday i'll have one,
Cheers....

also i do not own these art
https://elwiki.net/w/Noah/Gallery

“Life without music would seem to be a terrible mistake”

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Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

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Machine Learning for Operational Analytics and Business Intelligence

O'Reilly Radar