Understanding urban gentrification through machine learning

Understanding Career Progression in Baseball Through Machine Learning

Professional baseball players are increasingly guaranteed expensive long-term contracts, with over 70 deals signed in excess of $90 million, mostly in the last decade. These are substantial sums compared to a typical franchise valuation of $1-2 billion. Hence, the players to whom a team chooses to give such a contract can have an enormous impact on both competitiveness and profit. Despite this,...

Understanding Signal Sequences with Machine Learning

Protein translocation, the transport of newly synthesized proteins out of the cell, is a fundamental mechanism of life. We are interested in understanding how cells recognize the proteins that are to be exported and how the necessary information is encoded in the so called “Signal Sequences”. In this paper, we address these problems by building a physico-chemical model of signal sequence recogn...

Machine Learning Through Data Mining

INTRODUCTION In dealing with information it often turns out that one has to face a huge amount of data, often not completely homogeneous and often without an immediate grasp of an underlying simple structure. Many records, each one instantiating many variables, are usually collected with the help of various technologies. Given the opportunity to have so many data not easy to correlate by the hu...

Understanding and Fighting Bullying With Machine Learning

Bullying, in both physical and cyber worlds, has been recognized as a serious health issue among adolescents. Given its significance, scholars are charged with identifying factors that influence bullying involvement in a timely fashion. However, previous social studies of bullying are handicapped by data scarcity. The standard psychological science approach to studying bullying is to conduct pe...

UNDERSTANDING MACHINE LEARNING From Theory to Algorithms