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  2. Mallet (software project) - Wikipedia

    en.wikipedia.org/wiki/Mallet_(software_project)

    MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, cluster analysis, information extraction, topic modeling and other machine learning applications to text.

  3. Apache Mahout - Wikipedia

    en.wikipedia.org/wiki/Apache_Mahout

    Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily on linear algebra. In the past, many of the implementations use the Apache Hadoop platform, however today it is primarily focused on Apache Spark .

  4. Data Version Control (software) - Wikipedia

    en.wikipedia.org/wiki/Data_Version_Control...

    DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines.

  5. Spring Framework - Wikipedia

    en.wikipedia.org/wiki/Spring_Framework

    Spring Roo is a community project which provides an alternative, code-generation based approach at using convention-over-configuration to rapidly build applications in Java. It currently supports Spring Framework, Spring Security and Spring Web Flow. Roo differs from other rapid application development frameworks by focusing on:

  6. Deeplearning4j - Wikipedia

    en.wikipedia.org/wiki/Deeplearning4j

    Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [ 2 ] [ 3 ] It is a framework with wide support for deep learning algorithms. [ 4 ] Deeplearning4j includes implementations of the restricted Boltzmann machine , deep belief net , deep autoencoder, stacked denoising autoencoder and recursive ...

  7. CatBoost - Wikipedia

    en.wikipedia.org/wiki/Catboost

    It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.

  8. Encog - Wikipedia

    en.wikipedia.org/wiki/Encog

    Encog is a machine learning framework available for Java and .Net. [1] Encog supports different learning algorithms such as Bayesian Networks, Hidden Markov Models and Support Vector Machines. However, its main strength lies in its neural network algorithms. Encog contains classes to create a wide variety of networks, as well as support classes ...

  9. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...