Topic:Machine learning
From Wikiversity
 Please help develop this page
This page was created, but so far, little content has been added. Everyone is invited to help expand and create educational content for Wikiversity. If you need help learning how to add content, see the editing tutorial and the MediaWiki syntax reference. To help you get started with content, we have automatically added references below to other Wikimedia Foundation projects. This will help you find materials such as information, media and quotations on which to base the development of "Machine learning" as an educational resource. However, please do not simply copy-and-paste large chunks from other projects. You can also use the links in the blue box to help you classify this page by subject, educational level and resource type. |
|
Welcome to the Department of Machine Learning!
As a broad subfield of artificial intelligence, machine learning is concerned with the development of algorithms and techniques that allow computers to "learn". At a general level, there are two types of learning: inductive, and deductive. Inductive machine learning methods extract rules and patterns out of massive data sets.
Some parts of machine learning are closely related to data mining and statistics. Machine learning research is focused on the computational properties of the statistical methods, such as their computational complexity.
Machine learning has a wide spectrum of applications including natural language processing, search engines, medical diagnosis, bioinformatics and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing and robot locomotion.
Contents |
[edit] Department news
- February 28, 2007 - Department founded!
[edit] Learning projects
decision tree, Naive Bayes, fuzzy logic, support vector machine
[edit] Research
[edit] Active participants
Sean Beckett (USR: Sbeckett2)
[edit] Wikibook textbooks
[edit] External links
[edit] Open source software (OSS)
- RapidMiner, a freely available open-source software for intelligent data analysis, knowledge discovery, data mining, machine learning, visualization, etc. featuring numerous feature generation and feature selection operators. Formerly known as Yale.
- Weka, a Java software package including a collection of machine learning algorithms for data mining tasks.
