pemMachine Learning An Applied Mathematics Introductionem covers the essential mathematics behind all of the following topicsp ul liemKem Nearest Neighbours li liemKem Means Clusteringli liNa ve Bayes Classifierli liRegression Methodsli liSupport Vector Machinesli liSelf-Organizing Mapsli liDecision Treesli liNeural Networksli liReinforcement Learningli ul pThe book includes many real-world examples from a variety of fields includingp ul lifinance volatility modellingli lieconomics interest rates, inflation and GDPli lipolitics classifying politicians according to their voting records, and using speeches to determine whether a politician is left or right wingli libiology recognising flower varieties, and using heights and weights of adults to determine genderli lisociology classifying locations according to crime statisticsli ligambling fruit machines and Blackjackli libusiness classifying the members of his own website to see who will subscribe to his magazine li ul pPaul Wilmott brin