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  2. ELKI - Wikipedia

    en.wikipedia.org/wiki/ELKI

    elki-project.github.io: ... for anomaly detection in spaceflight operations, [5] ... The source code is written with extensibility and reusability in mind, but is ...

  3. scikit-multiflow - Wikipedia

    en.wikipedia.org/wiki/Scikit-multiflow

    It features a collection of classification, regression, concept drift detection and anomaly detection algorithms. It also includes a set of data stream generators and evaluators. scikit-multiflow is designed to interoperate with Python's numerical and scientific libraries NumPy and SciPy and is compatible with Jupyter Notebooks .

  4. Deeplearning4j - Wikipedia

    en.wikipedia.org/wiki/Deeplearning4j

    Real-world use cases for Deeplearning4j include network intrusion detection and cybersecurity, fraud detection for the financial sector, [21] [22] anomaly detection in industries such as manufacturing, recommender systems in e-commerce and advertising, [23] and image recognition. [24]

  5. BigDL - Wikipedia

    en.wikipedia.org/wiki/BigDL

    In other projects Wikidata item; ... Anomaly detection. RANSAC; k-NN; ... BigDL has its source code hosted on GitHub. [3] Features

  6. Zeek - Wikipedia

    en.wikipedia.org/wiki/Zeek

    Zeek analyzers perform application layer decoding, anomaly detection, signature matching and connection analysis. [13] Zeek's developers designed the software to incorporate additional analyzers. The latest method for creating new protocol analyzers relies on the Spicy framework.

  7. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    ELKI is an open-source Java data mining toolkit that contains several anomaly detection algorithms, as well as index acceleration for them. PyOD is an open-source Python library developed specifically for anomaly detection. [56] scikit-learn is an open-source Python library that contains some algorithms for unsupervised anomaly detection.

  8. Caffe (software) - Wikipedia

    en.wikipedia.org/wiki/Caffe_(software)

    Yangqing Jia created the Caffe project during his PhD at UC Berkeley, while working the lab of Trevor Darrell. [6] The first version, called "DeCAF", made its first appearance in spring 2013 when it was used for the ILSVRC challenge (later called ImageNet). The library was named Caffe and released to the public in December 2013. [6]

  9. MindSpore - Wikipedia

    en.wikipedia.org/wiki/MindSpore

    On April 24, 2024, Huawei's MindSpore 2.3.RC1 was released to open source community with Foundation Model Training, Full-Stack Upgrade of Foundation Model Inference, Static Graph Optimization, IT Features and new MindSpore Elec MT (MindSpore-powered magnetotelluric) Intelligent Inversion Model.