Weka

Weka, an open source software, is a set of machine learning algorithms for data mining tasks. The algorithms can be applied directly to a dataset or called from your own Java code. It is also well-suited for developing new machine learning schemes because it is fully implemented in the Java programming language, and also supports several standard data mining tasks. For those who haven’t programmed for a while, Weka, with its graphical interface, provides the easiest transition into the world of Data Science. For users with Java programming experience, it’s possible to embed your own code in the library.

To begin with, WEKA is a data analysis and machine learning library written in Java. The name stands for Waikato Environment for Knowledge Analysis. It is a project of Waikato University in New Zealand. Weka is a set of state-of-the-art machine learning algorithms and data preprocessing tools.

The WEKA suite is well suited for those just beginning to learn about data mining and machine learning, since WEKA can be run via a graphical interface that does not require you to write code. WEKA contains the necessary data preprocessing tools, data visualization, and machine learning algorithms.

The Weka installation folder has a data folder that contains datasets that can be used for practice.

If you like WEKA and want to learn it better, there are 3 courses from the creators of WEKA at futurelearn.com – Data Mining with Weka, More Data Mining with Weka, Advanced Data Mining with Weka. You can join the courses for free, but then access to the courses will be limited. The video lessons of these courses are also available on YouTube.