Difference between revisions of "DataMining/spring2020"
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| − | {{DISPLAYTITLE:CSC314 - Data Mining}} | + | {{DISPLAYTITLE:CSC314 - Data Mining (Spring 2020)}} |
== Course Information == | == Course Information == | ||
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|syllabus=[[media:RobertLowe-CSC314-Spring2020-01.pdf|Spring 2020 Syllabus]] | |syllabus=[[media:RobertLowe-CSC314-Spring2020-01.pdf|Spring 2020 Syllabus]] | ||
}} | }} | ||
| + | |||
| + | == Materials and Links == | ||
| + | * [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://rstudio.cs.maryvillecollege.edu/ R-Studio] | ||
| + | * [https://learnxinyminutes.com/docs/r/ Learn R in 15 Minutes] | ||
== Slides and Examples == | == Slides and Examples == | ||
| + | * [[media:CSC314-Spring2020-01-Introduction-handout.pdf|Introduction]] | ||
| + | * [[media:CSC314-Spring2020-chap1.pdf|Chapter 1 Slides]] | ||
| + | * [[media:CSC314-Spring2020-Iris-EDA-1.pdf|Introduction to R and Iris EDA part 1]] | ||
| + | * [http://www.dataminingbook.info/pmwiki.php/Main/BookPathUploads?action=download&upname=slides-chap2.pdf Chapter 2 Slides] | ||
| + | * [[media:CSC314-Spring2020-Iris-EDA-2.pdf|Iris EDA part 2]] | ||
| + | * [[media:CSC314-Spring2020-Iris-Categorical-EDA.pdf|Iris Categorical EDA]] | ||
| + | * [[media:CSC314-Spring2020-EigenPets-Part1.pdf|Eigen Pets Part 1]] | ||
| + | * [http://www.dataminingbook.info/pmwiki.php/Main/BookPathUploads?action=download&upname=slides-chap8.pdf Chapter 8 - Itemset Mining] | ||
| + | * [[media:CSC314-Spring2020-Itemset.pdf|Itemset Mining]] | ||
| + | |||
| + | == Homework == | ||
| + | * [[DataMining/spring2020/hw1| Homework 1]] (due January 30) | ||
| + | * [[DataMining/spring2020/hw2| Homework 2]] (due February 11) | ||
| + | * [[DataMining/spring2020/hw3| Homework 3]] (due March 5) | ||
| + | |||
| + | == Projects == | ||
| + | * [[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
- Data Mining and Analysis Fundamental Concepts and Algorithms] by Mohammed J. Zaki Wagner Meira, Jr.
- Sign Up for a Shell Account
- R-Studio
- Learn R in 15 Minutes
Slides and Examples
- Introduction
- Chapter 1 Slides
- Introduction to R and Iris EDA part 1
- Chapter 2 Slides
- Iris EDA part 2
- Iris Categorical EDA
- Eigen Pets Part 1
- Chapter 8 - Itemset Mining
- Itemset Mining
Homework
- Homework 1 (due January 30)
- Homework 2 (due February 11)
- Homework 3 (due March 5)
Projects
- Project 1 (Due March 10)
