Home Conferences Data & Text Mining: Business Analytics at work - Singapore

Data & Text Mining: Business Analytics at work - Singapore

Join us in Singapore!

PROFILE Master Degrees
EVENT TYPE Conferences
EVENT FORMAT Face to Face events
DATE 17th October 2019
TIME 18:30 - 20:00 (GMT +08:00)
LANGUAGE English
Data & Text Mining: Business Analytics at work - Singapore

The widespread availability of data has contributed to the creation of tools for combining data science and business strategy to make data-driven decisions in complex environments.  

This seminar is centered on the presentation and practical demonstration of how data visualization, along with statistical modeling and interpretation are used to generate new and powerful insight. We will exemplify the power of business analytics through a few cases, e.g., the prediction and identification of cardiovascular risk factors, the classification of tweets based on sentiment analysis, and the use of a novel text-mining method to map words, sentences, and documents into vectors. Using Amazon Mechanical Turk, we will illustrate how, e.g., tweets and conversations can be classified or grouped together, thus getting new insight into the dynamics of the ongoing conversation about a person, a company, or a topic on the social network.  

 

During the session, we will run a live demo using python to clearly evince the power of business analytics at work. 

 

ABOUT THE SPEAKER 

 

Marco Caserta received his Ph.D. in Industrial Engineering and Operations Research from the University of Illinois (USA), after earning an MSc in Management Engineering from the Politecnico di Milano (Italy). Prior to joining IE, Marco has held faculty positions at Hamburg University, Germany, Tecnológico de Monterrey, Mexico, and the University of Illinois, USA. He teaches statistics at IE University and optimization related courses at IE 

Business School. 

His main research interest is focused on the design and development of metaheuristic based algorithms for very large-scale real-world optimization problems, with a special focus on data mining, logistics, telecommunication, and transportation-related problems. He has published a number of papers in international journals in the area of operations research/management science.