Machine learning.

Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Or to put it in laymen terms. Or to put it in laymen terms, it trains a "machine" to "learn" a specific trick.

You can start using this library by downloading one of the archives, cloning the repository, or installing it via Composer.

Data pre-processing

An important first step in machine learning is preparing the dataset, since this is the foundation of learing your machine. Analyze the dataset, identify the missing values and norrmalize the nominal values are a few actions that need to be addressed before starting to train your system.

Learning approaches

The hardest step in machine learning is not to train the system, but to find the most suitable approach. This depends on the datatset and the goal (which by itself, can be a difficult task). If you want to build a profiling system you might want to considder clustering, or you want to discover something new you can choose an unsupervised learning approach. If you want to "predict" a certain outcome, supervised learning is your best friend.

Support or Contact

Having trouble with the library? Check out the documentation at http://machinelearning.readthedocs.org/en/latest/ or contact info@willembressers.nl and we’ll help you sort it out.