Showing 4 open source projects for "learning classifier system"

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  • 1
    DVC

    DVC

    Data Version Control | Git for Data & Models

    DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,...
    Downloads: 0 This Week
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  • 2
    ungit

    ungit

    A tool to simplify the use of git, on any platform, anywhere

    Git is known for being a versatile distributed source control system that is a staple of many individuals, communities, and even for the City of Chattanooga to crowd source bicycle parking locations. However, it is not known for userfriendliness or easy learning curve. Ungit brings user friendliness to git without sacrificing the versatility of git. Git and github both supports PGP signing. Within Ungit these features can be enabled.
    Downloads: 4 This Week
    Last Update:
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  • 3
    GitLab CE Server For Local Intranets

    GitLab CE Server For Local Intranets

    The Free & Popular Community git Server in a Complete Virtual Machine

    This VM is created for 2 reasons: 1. Very little initial setup work required to make a GIT Server live, within minutes. 2. This system should keep running for Years, without requiring Updates / Breakages. If you are new to Virtual Machines, then please watch the Video below ( taken from my other project. just replace td with gi wherever mentioned ) After starting this VM, please login to its administration panel with: Website Address: https://gi.local/ ( Accept Any Warnings due to...
    Downloads: 0 This Week
    Last Update:
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  • 4
    Albedo

    Albedo

    A recommender system for discovering GitHub repos

    Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. ...
    Downloads: 0 This Week
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