DM1: Introduction: Machine Learning and Data Mining - Sorry

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Summary: • Technology trends lead to data flood • data mining is needed to make sense of data • Data Mining has many applications, successful and not • Knowledge Discovery Process • Data Mining Tasks • classification, clustering, … 38
Page 1 and 2: Machine Learning, Data Mining, and
Page 3 and 4: Lesson Outline •Introduction: Dat
Page 5 and 6: Big Data Examples • Europe's Very
Page 7 and 8: From terabytes to exabytes to …
Page 9 and 10: Data Growth In 2 years, the size of
Page 13 and 14: Application Areas What do you think
Page 15 and 16: Customer Attrition: Case Study •S
Page 17 and 18: Customer Attrition Results • Veri
Page 19 and 20: Credit Risk - Results • Banks dev
Page 21 and 22: Successful e-commerce - Case Study
Page 23 and 24: Genomic Microarrays - Case Study Gi
Page 25 and 26: Security and Fraud Detection - Case
Page 29 and 30: Related Fields Machine Learning Vis
Page 31 and 32: Knowledge Discovery Process flow, a
Page 35: Data Mining Tasks: Classification L
Page 39: 1997 1998 1999 2000 2001 2002 2003

DM1: Introduction: Machine Learning and Data Mining - Sorry

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