Skip to content

Work in course at The technical University of Denmark in Machine Learning and Data Mining.

Notifications You must be signed in to change notification settings

frksteenhoff/02450_MachineLearning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

02450 - Introduction to Machine Learning and Data Mining

Contains a lot of machine learning methods for preprocessing data, splitting into test and training sets evaluate the result etc.

In order to run the code you need:

  • python 2.7 or 3.x

Brief overview of content

Tags: Machine learning, supervised learning, Libraries: sklearn, numpy, scipy, graphviz, io, re, pandas, matplotlib ..

Areas: Principal Component Analysis, Classification, Summary Statistics, Cross-validation, One-out-of-K coding, Probability, K Nearest Neigbors, Decision Trees, Attributes, Performance Evaluation, Visualization

About

Work in course at The technical University of Denmark in Machine Learning and Data Mining.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published