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Tom Fawcett

Links: * Email * Twitter * LinkedIn * ORCID id: 0000-0002-9074-7516

Tom Fawcett is an active member of the machine learning and data mining communities.

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He is co-author, with Foster Provost, of the O’Reilly book “Data Science for Business: What you need to know about data mining and data-analytic thinking”, first published in July 2013. It is O’Reilly’s best-selling data science book, being used as a textbook by more than 150 universities around the world, and translated into five languages. It has been listed as required reading by Forbes and Harvard Business Review, and has appeared on best-book lists for understanding data science.

Dr. Fawcett has a Ph.D. in machine learning from UMass-Amherst and has worked in industrial research (GTE Laboratories, NYNEX/Verizon Labs, HP Labs, etc.). In his career he has published numerous conference and journal papers in machine learning. He has been an editor and editorial board member of the Machine Learning journal for about ten years. In 2003 he co-chaired the program of the premier machine learning conference (ICML) and has organized many workshops and journal special issues. He received a Best Paper Award from KDD, a SCOPUS Award (most cited paper) from Pattern Recognition Letters, and a President’s Award from Verizon.

Dr. Fawcett is on the editorial boards of the Machine Learning Journal, Big Data, and Data Mining and Knowledge Discovery.

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Tom knows HTML but is not skilled enough to design a careful, professional-looking website.