What if you don’t have enough data and still want to make predictions? Small data brings a completely different set of problems than big data. Instead of dealing with scale and efficiency, the game here is to draw statistical significant results from very few noisy examples. The problems lure the scientists into a completely new world of Statistics, over-fitting, temporal affects, natural language processing with prior knowledge of domains, learning from a single example. The small data and its problems revive the old AI paradigm of deductive reasoning. In this talk Kira will discuss the algorithmic approaches in this field, and their application to the field of sales prediction.
Dr. Radinsky is the CTO and cofounder of SalesPredict, a sales technology company, where she is pioneering artificial intelligence based, predictive analytics solutions that transform the way companies do business.
Dr. Kira Radinsky is one of the up and coming voices in the data science community, pioneering the field of Web Dynamics and Temporal Information Retrieval. Her work focuses on the intersection of predictive data mining and the construction of algorithms that leverage web-found information and external dynamics to predict future events. A graduate of the Technion-Israel Institute of Technology, Dr. Radinsky gained international recognition for her work there and at Microsoft Research where she developed predictive algorithms that recognized the early warning of globally impactful events, (e.g. riots or diseases.)
In 2013, Kira Radinsky was named to the prestigious “35 Young Innovators Under 35”, as chosen by the MIT Technology Review.