Richmond Data Science Community is where people with same interests come and discuss the topic of data science. This group helps educates people in the field of data visualizations, machine learning, applied mathematics and statistics. We encourage our members to give a talk, present or come and share the knowledge and experiences on data analytics related topics. We encourage students, data professionals, programmers, developers and interested people to join and make this community smarter and successful. Our goal is to build a strong data community where we can learn things from each others, network with other members and solve challenging problems together using data science skills.
6 pm – 6:45 pm Networking and Refreshments
Food and drinks will be kindly sponsored by CapTech Consulting
6:45 - 8 pm Talk by Andrew Clark and Q&A
Machine learning algorithms are permeating our world. With applications in banking, investing, social media, advertising, and crime prevention, to name a few, these little black boxes are increasingly being used to inform and drive decisions about our lives and businesses. Machine Learning Risk Management is an often overlooked aspect of creating, deploying, and monitoring machine learning applications. Andrew will explain the dangers associated with an absence of controls during the machine learning process. He will then demonstrate how controls prevent modeling biases and suggest ways to develop and deploy machine learning applications with a control-centric, engineered approach.
Andrew Clark is a Data Economist at BlockScience; engineering research, and development, and analytics firm focused on the design and analysis of complex networks. At BlockScience Andrew creates ecosystem economic design specifications by simulating the designed ecosystem using Python-based methods. Employing mathematical engineering technologies, he creates novel solutions by utilizing time-tested systems engineering practices to solve business problems. He received Bachelors in Business Administrations, Master in Data Science, and a Ph.D. student in Economics at the University of Reading.