Difference between revisions of "DataMining/spring2020"

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== Materials and Links ==
 
== Materials and Links ==
* [http://www.dataminingbook.info/ Data Mining and and Analysis Fundamental Concepts and Algorithms]] by  Mohammed J. Zaki Wagner Meira, Jr.
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* [http://www.dataminingbook.info/ Data Mining and Analysis Fundamental Concepts and Algorithms]] by  Mohammed J. Zaki Wagner Meira, Jr.
 
* [http://cs.maryvillecollege.edu/signup Sign Up for a Shell Account]
 
* [http://cs.maryvillecollege.edu/signup Sign Up for a Shell Account]
 
* [http://rstudio.cs.maryvillecollege.edu/ R-Studio]
 
* [http://rstudio.cs.maryvillecollege.edu/ R-Studio]
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== Slides and Examples ==
 
== Slides and Examples ==
* [[media:CSC314-Spring2020-01-Introduction.pdf|Introduction]]
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* [[media:CSC314-Spring2020-01-Introduction-handout.pdf|Introduction]]
 
* [[media:CSC314-Spring2020-chap1.pdf|Chapter 1 Slides]]
 
* [[media:CSC314-Spring2020-chap1.pdf|Chapter 1 Slides]]
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* [[media:CSC314-Spring2020-Iris-EDA-1.pdf|Introduction to R and Iris EDA part 1]]
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* [http://www.dataminingbook.info/pmwiki.php/Main/BookPathUploads?action=download&upname=slides-chap2.pdf Chapter 2 Slides]
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* [[media:CSC314-Spring2020-Iris-EDA-2.pdf|Iris EDA part 2]]
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* [[media:CSC314-Spring2020-Iris-Categorical-EDA.pdf|Iris Categorical EDA]]
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* [[media:CSC314-Spring2020-EigenPets-Part1.pdf|Eigen Pets Part 1]]
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* [http://www.dataminingbook.info/pmwiki.php/Main/BookPathUploads?action=download&upname=slides-chap8.pdf Chapter 8 - Itemset Mining]
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* [[media:CSC314-Spring2020-Itemset.pdf|Itemset Mining]]
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== Homework ==
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* [[DataMining/spring2020/hw1| Homework 1]] (due January 30)
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* [[DataMining/spring2020/hw2| Homework 2]] (due February 11)
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* [[DataMining/spring2020/hw3| Homework 3]] (due March 5)
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== Projects ==
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* [[DataMining/spring2020/project1| Project 1]] (Due March 10)

Latest revision as of 12:05, 3 March 2020


Course Information

Code CSC3140
Name Data Mining
Credit(s) 3
Prerequisites CSC313 and MTH321
Offered Every Spring
Catalog Description Data mining is concerned with the extraction of information from large amounts of data. This project-based course introduces the concepts, issues, tasks and techniques of data mining. Topics include data preparation and feature selection, classification, clustering, evaluation and validation, and data mining applications.
Syllabus Spring 2020 Syllabus
Other Offerings DataMining/offerings

Materials and Links

Slides and Examples

Homework

Projects