# Difference between revisions of "DataMining/spring2020"

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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.pdf|Introduction]] | + | * [[media:CSC314-Spring2020-01-Introduction-handout.pdf|Introduction]] |

* [[media:CSC314-Spring2020-chap1.pdf|Chapter 1 Slides]] | * [[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)