CS 506: Data Science Tools

[github]

Lectures

Lecture 1 - Intro to Python

Lecture 2 - Getting Started

Lecture 3 - Pandas

Lecture 4 - Distance Functions | Slides

Lecture 5 - k-means clustering

Lecture 6 - Clustering

Lecture 7 - SVD | Slides

Lecture 8 - SVD in practice

Lecture 9 - Other clustering algorithms | [Hierarchical-Slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-9/hierarchical.pdf?raw=true) | [Density-slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-9/density-based-clustering.pdf?raw=true)

Lecture 10 - Web scraping slides

Lecture 11 - Classification | [Slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-11/evaluation.pdf?raw=true)

Lecture 12 - Linear Regression

Lecture 13 - Logistic Regression

Lecture 14 - SVM-Boosting | [Slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-14/svm-boosting.pdf?raw=true)

Lecture 15 - Text Analysis and Topic Modeling

Lecture 16 - Introduction to graph analysis

Lecture 17 - Introduction to graph analysis

Lecture 18 - Node Centralities | [Centrality-slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-18/Centrality-Measures.pdf?raw=true)

Lecture 19 - Network Visualization

Lecture 20 - Community detection | [Cuts-slides] (https://github.com/dataminingapp/dataminingapp-lectures/blob/master/Lecture-20/cuts.pdf?raw=t
rue)