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  • 1
    Self Organization of an adaptive learning framework for pervasive graph structures from grids, utilities to semantic governance. Business, performance and provisioning assurance are converged with EGA, ITIL, eTOM,SOX, HIPPA, CobiT and AC
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  • 2
    An adaptive mini database learns algorithmic operations for data intensive algebraic computational methods within a pervasive computing graph. It also provides generic structures and algorithms as a data fabric.
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  • 3
    The central aim of OrkAPI is to be an interface to any kind of Ork-related data within Java. It also features a GUI that can assist in creating a move and inspecting the collected data. There are many points to extend OrkAPI with "Plugin" classes.
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  • 4
    PlexBench is a cross-platform, web-enabled, analysis tool that is driven by a scalable backpropagation feed-forward neural network. It uses embedded Perl for scripting and is written in the style of an in-process Component Object Model (COM) C++ program.
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    Our Free Plans just got better! | Auth0

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  • 5
    PyPlayground is an environment for developing algorithms involving movement in a space of up to three dimensions using Python.
    Downloads: 0 This Week
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  • 6
    Quint Code

    Quint Code

    Structured reasoning framework for Claude Code, Gemini, and Cursor

    Quint Code is a structured reasoning and decision-support framework aimed at making AI-assisted software engineering and decision workflows more rigorous and auditable. It implements the First Principles Framework (FPF) to guide users and AI tools through hypothesis generation, logical verification, evidence gathering, and documented decision making, reducing reliance on ad hoc or “vibe” coding. Instead of accepting the first plausible answer generated by an AI assistant, Quint Code encourages generating multiple competing hypotheses, verifying them, and validating them against real evidence stored in a structured “knowledge base” within your project. It supports a cycle of abduction, deduction, and induction backed by CLI commands (like /q1-hypothesize, /q2-verify, /q3-validate, etc.) that create a persisting audit trail in a .quint/ directory.
    Downloads: 0 This Week
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  • 7
    Robot Controlling System (RCS) - is a .NET-oriented software group for controlling remote mechanical objects, debuging and programming them by .NET-languages
    Downloads: 0 This Week
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  • 8
    SEAGE
    Search Agents - a framework for collaboration of meta-heuristic agents
    Downloads: 0 This Week
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  • 9
    Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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  • 10
    Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
    Downloads: 0 This Week
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  • 11
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.
    Downloads: 0 This Week
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  • 12
    A software toolkit that implements the CoSy Architecture Schema for developing integrated intelligent robotic systems. The toolkit focuses on supporting on a space of information-processing architectures based on shared working memories.
    Downloads: 0 This Week
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  • 13
    The Duine Framework allows one to develop prediction engines for recommender systems. It contains a set of prediction techniques, a way to combine these techniques and a profile manager. The framework has a plug-in architecture, allowing customization.
    Downloads: 0 This Week
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  • 14
    Maiden-core is a Linux kernel robotics API module, extensible in Erc. The Maiden Project also documents and develops the Maiden architecture for mobile robots, a set of (optional) designs and standards for robots using the Maiden-core API.
    Downloads: 0 This Week
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  • 15
    UnionML

    UnionML

    Build and deploy machine learning microservices

    Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. This helps you maintain consistent code across your ML stack, from training to prediction logic.
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  • 16
    agents
    Java framework for agent based application development
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  • 17
    CARTAGO-WS is a platform for developing SOA applications based on Web Services exploiting agent programming models and technologies.
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  • 18
    Java framework for face detection and face recognition based on different plugin and filter types. Includes Eigenfaces in pure Java, OpenCV detection via JNI, integration of the Betaface.com Web Service, skin color filter, Adobe XMP Export and a nice GUI
    Downloads: 0 This Week
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  • 19
    jSemanticService is a lightweight framework that allows to use Rules and Semantics in Services or Applications using Annotations. Features: jBoss Rules (Drools 4.0) as Business Rules Engine provider. Full support of Annotations, Spring, Flex/Blaze DS.
    Downloads: 0 This Week
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  • 20
    libFuzzyEngine++
    A C++ port of Fuzzy Engine for Java in a form of a library. The Fuzzy Engine is a Fuzzy Logic implementation, which can be used, for instance, to create fuzzy controllers. See also: http://sf.net/projects/fuzzyengine for an updated version for Java.
    Downloads: 0 This Week
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  • 21
    myMAS is a framework for writing distributed, agent based Java applications.
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  • 22
    Open Source Semantic Web Search Engine Software: If two machines anywhere on the web can agree on the same definition of a digital service or digital good, then machine to machine transactions can use this lingua franca to transact on the users behalf.
    Downloads: 0 This Week
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  • 23
    stkpp

    stkpp

    C++ Statistical ToolKit

    STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template classes in C++ and is suitable for projects ranging from small one-off projects to complete data mining application suites.
    Downloads: 0 This Week
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  • 24
    towhee

    towhee

    Framework that is dedicated to making neural data processing

    Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data.
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  • 25
    Procedural content generation of deterministic and complex entities, with properties and other entities inside, defined by an editable XML file, along with a framework to simulate actions, compositions, and interactions of entities.
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