diff --git a/index.html b/index.html index f68a0ee..044987e 100644 --- a/index.html +++ b/index.html @@ -1,207 +1 @@ - - - - - Weka 3 - Data Mining with Open Source Machine Learning Software in Java - - - - - - - - - - - - -
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WEKA

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The workbench for machine learning

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Weka is tried and tested open source machine learning software that can be accessed through a graphical user interface, standard terminal applications, or a Java API. It is widely used for teaching, research, and industrial applications, contains a plethora of built-in tools for standard machine learning tasks, and additionally gives transparent access to well-known toolboxes such as scikit-learn, R, and Deeplearning4j. - -

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Getting Started

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Video from Josh Gordon, Developer Advocate for @GoogleAI.

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Machine Learning without Programming

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Weka can be used to build machine learning pipelines, train classifiers, and run evaluations without having to write a single line of code:

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Open a dataset

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First, we open the dataset that we would like to evaluate.

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Choose a classifier

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Second, we select a learning algorithm to use, e.g., the J48 classifier, which learns decision trees.

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Evaluate predictive accuracy

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Finally, we run a 10-fold cross-validation evaluation and obtain an estimate of predictive performance.

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- Deep Learning with Weka -
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Deep Learning with WEKA

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WekaDeeplearning4j is a deep learning package for Weka. Deep neural networks, including convolutional networks and recurrent networks, can be trained directly from Weka's graphical user interfaces, providing state-of-the-art methods for tasks such as image and text classification.

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WEKA Interoperability

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WEKA can be integrated with the most popular data science tools.

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R

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Weka models can be used, built, and evaluated in R by using the RWeka package for R; conversely, R algorithms and visualization tools can be invoked from Weka using the RPlugin package for Weka.

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Python

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Weka's functionality can be accessed from Python using the Python Weka Wrapper. Conversely, Python toolkits such as scikit-learn can be used from Weka.

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Spark

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For running Weka-based algorithms on truly large datasets, the distributed Weka for Spark - package is available. It makes it possible to train - any Weka classifier in Spark, for example.

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- Weka is proudly brought to you by the Machine Learning Group at the University of Waikato. -
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