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**RapidMiner Studio**:Software platform with integrated environment for machine learning, deep learning, text mining, and predictive analytics. The RapidMiner (free) Basic Edition, which is limited to 1 logical processor and 10,000 data rows, is available under the AGPL license.**GNU Octave**:Scientific Programming Language, powerful mathematics-oriented syntax with built-in plotting and visualization tools, Free software, runs on GNU/Linux, macOS, BSD, and Windows also Drop-in compatible with many Matlab scripts**IPNNL Software**:Image Processing and Neural Networks Lab**Sciengy RPF**:Windows application for data mining with self-organizing neural networks. It works with text data files and has convenient user interface. Is solves data mining tasks of class Recognition, continuous value Prediction, and time series Forecast**Random Forests**:Random Forests(tm) is a trademark of Leo Breiman and Adele Cutler (classification/clustering, regression, survival analysis and graphics)**Develve**:Statistical software for fast and easy interpretation of experimental data in science and R&D in a technical environment. This statistical package helps with analysis and prevents making false assumptions. In short it makes statistics faster and easier, suitable for less experience users but advanced enough for more demanding users.**Weka**:Collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.**KEEL (Knowledge Extraction based on Evolutionary Learning)**:Open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks. KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms. It contains a wide variety of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, among others), computational intelligence based learning algorithms, hybrid models, statistical methodologies for contrasting experiments and so forth.**OpenNN (Open Neural Networks)**:Open source class library written in C++ programming language which implements neural networks, a main area of machine learning research.**Orange Data Mining**:Open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox.**Apache PredictionIO**:Open source Machine Learning Server built on top of state-of-the-art open source stack for developers and data scientists create predictive engines for any machine learning task.**TensorFlow**:Open source software library for machine learning across a range of tasks, and developed by Google to meet their needs for systems capable of building and training neural networks to detect and decipher patterns and correlations, analogous to the learning and reasoning which humans use. TensorFlow was originally developed by the Google Brain team for internal Google use before being released under the Apache 2.0 open source license on November 9, 2015.**Dataiku**:(Free Edition) Collaborative data science platform to turn raw data into predictions.**R**:free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS**RStudio**:RStudio makes R easier to use. It includes a code editor, debugging & visualization tools, the RStudio Desktop(Open source License) is Free**MATLAB**:is a multi-paradigm numerical computing environment. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, C#, Java, Fortran and Python.**Jupyter**:is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.**Wolfram webMathematica**:Websites with sliders and other interactive controls compute new results when parameters change. Graphics, including 3D images, can be rotated in the browser. It is all powered by Mathematica computation and visualization capabilities and webMathematica robust, automatic server deployment that scales for high traffic and works seamlessly with modern web standards and services.