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ISYE-6180: Knowledge Discovery with Data Mining
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< meta property = "og:description" content = "Data mining is the computationally intelligent extraction of information from large databases. It is the process of automated presentation of patterns, rules, and functions from large data bases to make crucial business decisions. This course takes a multi-disciplinary approach to data mining and knowledge discovery involving statistics, rule and tree induction, neural networks, genetic algorithms, visualization and fuzzy logic. The course is project driven and puts a special emphasis on the use of computational intelligence for scientific data mining related to drug design and bioinformatics." >
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Knowledge Discovery with Data Mining
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ISYE-6180
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Data mining is the computationally intelligent extraction of information from large databases. It is the process of automated presentation of patterns, rules, and functions from large data bases to make crucial business decisions. This course takes a multi-disciplinary approach to data mining and knowledge discovery involving statistics, rule and tree induction, neural networks, genetic algorithms, visualization and fuzzy logic. The course is project driven and puts a special emphasis on the use of computational intelligence for scientific data mining related to drug design and bioinformatics.
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3 credits
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Prereqs:
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none
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Offered as Cross-Listing Only
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No Term Data
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Simple View
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Detailed View
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< th class = "spring season-label" > Spring< / th >
< th class = "summer season-label" colspan = "2" > Summer< / th >
< th class = "fall season-label" > Fall< / th >
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< th colspan = "2" > < / th >
< th class = "summer2 midsum-label" > (Session 1)< / th >
< th class = "summer3 midsum-label" > (Session 2)< / th >
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< th class = "year" > 2023< / th >
< td class = "term spring not-offered" >
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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< th class = "year" > 2022< / th >
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< th class = "year" > 2021< / th >
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< th class = "year" > 2020< / th >
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Knowledge Discovery With Data Mining (3c)
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< li > Mark J Embrechts< / li >
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Seats Taken: 5/20
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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< th class = "year" > 2019< / th >
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Knowledge Discovery With Data Mining (3c)
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< li > Mark J Embrechts< / li >
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Seats Taken: 17/20
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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Knowledge Discovery With Data Mining (3c)
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< li > Mark J Embrechts< / li >
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< span class = "course-capacity" >
Seats Taken: 0/20
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< td class = "term fall not-offered" >
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< th class = "year" > 2017< / th >
< td class = "term spring not-offered" >
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term spring not-offered" >
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< td class = "term fall not-offered" >
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Knowledge Discovery With Data Mining (3c)
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< li > Mark J Embrechts< / li >
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Seats Taken: 4/30
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< td class = "term fall not-offered" >
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< th class = "year" > 2014< / th >
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Knowledge Discovery With Data Mining (3c)
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< li > Mark J Embrechts< / li >
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Seats Taken: 19/30
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< td class = "term fall not-offered" >
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< span class = "term-course-info" >
Knowldge Discovry W/datamining (3c)
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< li > Mark J Embrechts< / li >
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< span class = "course-capacity" >
Seats Taken: 5/20
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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Knowldge Discovry W/datamining (3c)
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< li > Mark J Embrechts< / li >
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< span class = "course-capacity" >
Seats Taken: 16/30
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< td class = "term fall not-offered" >
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