Data-Mining

This site supports coding examples and homework for Introduction to Data Mining (CIS 3902) at Catawba College.
Getting Started:

1. Create and verify a Github Account.
   
2. Sign in to Github and access Catawba Data Mining on Github.
   
3. Follow instructions in Blackboard for the weekly assignments for class on https://github.com/catawba-data-mining/CIS-3902-Data-Mining/blob/main/README.md.
   

SPRING 2024 Zybook Data Mining

Markdown Tutorial Markdown Tutorial

### Add tocolab after github in the URL to open in Colab - Open Souce Google Colab Jupyter Notebook ### You will need to sign in to a google account for Colab to open ### if input is accessed via URL, no changes are needed to pd.read

Table of Contents (chapter content will be released each week)

Click on the link to access the assignment

1. Assignment 1 Mining the Classics
2. Assignment 2 Exploring Visualization NYC Fire Data
3. Assignment 3 Customer Segmentation Using Clustering: Mall Data
4. K-nearest neighbor clustering
5. Project
6. K Nearest Neighbor Example
7. Pycaret Multiclass Classification

The End

Other Resources

OPTIONAL TEXTBOOKS: These reference texts for the class are provided by UC Berkeley:

Data 8 Text: https://www.inferentialthinking.com/chapters/intro Computataional and Inferential Thinking (also available through creative commons license, UC Berkeley)

Data 100 Text: Principles and Techniques of Data Science http://www.textbook.ds100.org/intro.html

Examples from UC Berkeley and Catawba College CIS 3902 for reference and examples

Data 8 and Data 100

1. Chapter 1 Lab and HW 1
2. Chapter 2 Lab and HW 2
3. Chapter 7 Lab and HW 3
4. Chapter 11 Lab and HW 4
5. Chapter 15 & 16 Lab and HW 5
6. Titanic Lab HW 6
7. Decision Trees Random Forests Confusion Matrix HW 7
8. Project Deliverable 1 Predicting Shark Presence
9. Project Deliverable 2 Association Rules
10. Project Deliverable 3 Clustering

back to Table of Contents

The End