Data: born of humans, intended for human consumption, yet governed, analyzed, and processed by machines. For many of us, our mission in life is to derive insights from data. But more often than not, our tools produce results that are incomprehensible to humans. (Have you looked at a neural network lately?) In this talk, we will go on an adventure in data land, in order to understand data and data analysis models on their own turf. What does high dimensional feature space look like? How does “normalization” affect the look and feel of data? What is regularization? What exactly is my classifier saying to me? All these mysteries and more will be revealed. Enlightenment will follow promptly.
Alice is the Director of Data Science at GraphLab, a Seattle-based startup that offers powerful large-scale machine learning and graph analytics tools. She loves playing with data and enabling others to play with data. She is a tool builder and an expert in Machine Learning algorithms. Her research spans software diagnosis, computer network security, and social network analysis. Prior to joining GraphLab, she was a researcher at Microsoft Research, Redmond. She holds Ph.D. and B.A. degrees in Computer Science, and a B.A. in Mathematics, all from U.C. Berkeley.
Comments on this page are now closed.