EVA LEE
Virginia C. and Joseph C. Mello Chair and Professor, H. Milton Stewart School of Industrial & Systems Engineering, Georgia Tech, and Director of the Center for Operations Research in Medicine and HealthCare
Machine Learning and Big Data Analytics
The effect of big data is being felt everywhere, from business to science, from government to the arts. Information has gone from scarce to overabundant. This makes it possible to do many things that previously could not be done: uncover business trends, prevent diseases, combat crime, plus a multitude of other possibilities. Harnessing the data well may bring huge and innovative benefits, unlock new sources of economic value, provide fresh insights into science and provide policy makers with solid and convincing evidence to support their stands. Yet critical challenges lie ahead, including data security, privacy, and yet-to-be-discovered technology to effectively and efficiently analyze the data for business innovation. Multi-source data system modeling, machine learning and big data analytics play an increasingly important role in modern business enterprise. Many problems arising from multi-source data can be formulated into mathematical models and can be analyzed using sophisticated optimization, decision analysis, and computational techniques. In this tutorial, we will discuss various machine learning technologies, and share some of our successes in healthcare, defense, and service sector applications through innovation in predictive and big data analytics.
The effect of big data is being felt everywhere, from business to science, from government to the arts. Information has gone from scarce to overabundant. This makes it possible to do many things that previously could not be done: uncover business trends, prevent diseases, combat crime, plus a multitude of other possibilities. Harnessing the data well may bring huge and innovative benefits, unlock new sources of economic value, provide fresh insights into science and provide policy makers with solid and convincing evidence to support their stands. Yet critical challenges lie ahead, including data security, privacy, and yet-to-be-discovered technology to effectively and efficiently analyze the data for business innovation. Multi-source data system modeling, machine learning and big data analytics play an increasingly important role in modern business enterprise. Many problems arising from multi-source data can be formulated into mathematical models and can be analyzed using sophisticated optimization, decision analysis, and computational techniques. In this tutorial, we will discuss various machine learning technologies, and share some of our successes in healthcare, defense, and service sector applications through innovation in predictive and big data analytics.