6 projects for "knowledge graph" with 2 filters applied:

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  • 1
    The Machine & Deep Learning Compendium

    The Machine & Deep Learning Compendium

    List of references in my private & single document

    The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows. Originally created as a personal knowledge base, the repository evolved into a public educational resource designed to help learners explore the rapidly expanding machine learning ecosystem. ...
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  • 2
    Kodezi Chronos

    Kodezi Chronos

    Kodezi Chronos is a debugging-first language model

    ...Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation.
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  • 3
    The Algorithms - C++ #

    The Algorithms - C++ #

    Collection of various algorithms in mathematics, machine learning

    ...The project is part of the broader “The Algorithms” initiative, which maintains algorithm implementations in several programming languages to support education and knowledge sharing. Within the C++ repository, contributors implement algorithms across a wide range of fields including sorting, graph theory, number theory, machine learning, cryptography, and data structures. Each implementation is designed to be readable and well documented so that learners can understand the logic and structure behind each algorithm. ...
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  • 4
    AI_Tutorial

    AI_Tutorial

    A selection of learning materials, search, recommendation, advertising

    ...The curated content includes topics like recommendation systems, search engine architecture, neural networks, graph neural networks, and modern deep learning techniques. The goal of the project is to reduce information fragmentation by organizing valuable AI resources into structured sections that can be explored easily by learners and practitioners.
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    Secure File Transfer for Windows with Cerberus by Redwood

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  • 5
    AminePlatform

    AminePlatform

    Amine is a Multi-Layer Platform for the dev. of Intelligent Systems

    Amine is an Artificial Intelligence Multi-Layer Java Open Source Platform dedicated to the development of various kinds of Intelligent Systems and Agents (Knowledge-Based, Ontology-Based, Conceptual Graph -CG- Based, NLP, Reasoning and Learning, Natural Language Processing, etc.). Ontology, KB can be created and manipulated with various processes. CG theory is used as the main knowledge representation language. Amine provides two languages: PROLOG+CG which extends PROLOG with CG and Amine modules, and SYNERGY which is a visual activation/propagation based language. ...
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  • 6
    Literature of Deep Learning for Graphs

    Literature of Deep Learning for Graphs

    A comprehensive collection of recent papers on graph deep learning

    Literature of Deep Learning for Graphs is a curated repository that collects research papers and educational resources related to deep learning methods for graph-structured data. The project organizes important academic work covering topics such as graph neural networks, graph embeddings, knowledge graphs, and network representation learning. By structuring the literature into categories, the repository allows researchers to quickly identify influential papers in specific subfields of graph machine learning. ...
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