PPT-Introduction to Data Mining

Copyright 2013 Pearson Education Inc publishing as Prentice Hall 12 1 The Scope of Data Mining Data Exploration and Reduction Classification Classification Techniques Association Rule Mining. Mining. . for. . Building. . Energy. Management . Sustainable. Places 2014. Miguel Molina-Solana. Universidad de Granada. Outline. Introduction. Data . Mining. . for. . Energy. control. Big Data. Data . & Basic Data Analysis. Big Data . EveryWhere. ! . Lots of data is being collected . and warehoused . Web data, e-commerce. purchases at department/. grocery stores. Bank/Credit Card . transactions. Rafal Lukawiecki. Strategic Consultant, Project Botticelli Ltd. rafal@projectbotticelli.co.uk. Objectives. Overview Data Mining. Introduce typical applications and scenarios. Explain some DM concepts. Another Introduction to Data Mining. Course Information. 2. Knowledge Discovery in Data [and Data Mining] (KDD). Let us find something interesting!. Definition. := . “KDD is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” . Another Introduction to Data Mining. Course Information. 2. Knowledge Discovery in Data [and Data Mining] (KDD). Let us find something interesting!. Definition. := . “KDD is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” . Rafal Lukawiecki. Strategic Consultant, Project Botticelli Ltd. rafal@projectbotticelli.co.uk. Objectives. Overview Data Mining. Introduce typical applications and scenarios. Explain some DM concepts. 12-. 1. Data mining is a rapidly growing field of business analytics focused on better understanding of characteristics and patterns among variables in large data sets.. It is used to identify and understand hidden patterns that large data sets may contain.. Dr. . Kalpakis. , Fall 2017. 1. What is Data Science?. Data scientists, ". The Sexiest Job of the 21st Century. " (Davenport and . Patil. , Harvard Business Review, 2012). M. uch . of the data science explosion is coming from the tech-world. Instructor: . Yizhou. Sun. yzsun@ccs.neu.edu. January 6, 2013. Chapter 1. : Introduction. Course Information. Class . homepage: . http://. www.ccs.neu.edu/home/yzsun/classes/2013Spring_CS6220/index.htm. markovz@ccsu.edu Ingrid Russell University of Hartford irussell@hartford.edu Data Mining"Drowning in Data yet Starving for Knowledge" ???"Computers have promised us a fountain of wisdom but delivered markovzccsueduIngrid Russell University of HartfordirussellhartfordeduData MiningDrowning in Data yet Starving for Knowledge Computers have promised us a fountain of wisdom but delivered aflood of dat http://www.cs.uic.edu/~. liub. CS583, Bing Liu, UIC. 2. General Information. Instructor: Bing Liu . Email: liub@cs.uic.edu . Tel: (312) 355 1318 . Office: SEO 931 . Lecture . times: . 9:30am-10:45am. Another Introduction to Data Mining. Course Information. 2. Knowledge Discovery in Data [and Data Mining] (KDD). Let us find something interesting!. Definition. := . “KDD is the non-trivial process of identifying valid, novel, potentially... Bamshad Mobasher. DePaul University. 2. From Data to Wisdom. Data. The raw material of information. Information. Data organized and presented by someone. Knowledge. Information read, heard or seen and understood and integrated.