Weka is a collection of machine learning algorithms for data mining tasks; with its own GUI.



ELKI is described as ': "Environment for Developing KDD-Applications Supported by Index-Structures" is a development framework for data mining algorithms written in Java. It includes a large variety of popular data mining algorithms, distance functions and index structures' and is a Data Mining software in the business & commerce category. There are more than 10 alternatives to ELKI for a variety of platforms, including Linux, Mac, Windows, BSD and Web-based apps. The best ELKI alternative is R (programming language), which is both free and Open Source. Other great apps like ELKI are GNU Octave, MATLAB, SageMath and SciPy.
Weka is a collection of machine learning algorithms for data mining tasks; with its own GUI.



KEEL is an open source (GPLv3) Java software tool to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on. It contains a big collection of classical knowledge extraction algorithms, preprocessing...


Neural Designer is a software tool for advanced analytics. It includes tools for descriptive, diagnostic, predictive and prescriptive analytics. It allows you to get actionable insights resulting in smarter decisions and better business outcomes.




Apache Mahout is an Apache project to produce free implementations of distributed or otherwise scalable machine learning algorithms on the Hadoop platform. Mahout is a work in progress; the number of implemented algorithms has grown quickly, but there are still various...
SIMON is a powerful, flexible, open-source and easy to use knowledge discovery application. SIMON implements machine learning (autoML) and statistical data discovery features that will help you to illustrate dynamic relationships and provide you with a structural sense of your...




CuPy is an open-source array library for GPU-accelerated computing with Python. CuPy utilizes CUDA Toolkit libraries including cuBLAS, cuRAND, cuSOLVER, cuSPARSE, cuFFT, cuDNN and NCCL to make full use of the GPU architecture.
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