Showing 4 open source projects for "ekho-data"

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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.
    Downloads: 4 This Week
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  • 2
    PyScaffold

    PyScaffold

    Python project template generator with batteries included

    PyScaffold is a project generator for bootstrapping high-quality Python packages, ready to be shared on PyPI and installable via pip. It is easy to use and encourages the adoption of the best tools and practices of the Python ecosystem, helping you and your team to stay sane, happy and productive. The best part? It is stable and has been used by thousands of developers for over half a decade! Checkout out this demo project, which was set up using PyScaffold and if you are still not convinced...
    Downloads: 0 This Week
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  • 3
    GitFive

    GitFive

    Track down GitHub users

    GitFive is an open-source OSINT tool for investigating GitHub users and connecting publicly discoverable identity information. It can examine a username or email address and search for related GitHub accounts and identities. The tool analyzes repositories to uncover names, email addresses, local identities, and historical identity changes. It can generate possible email combinations and test them for matches. GitFive also identifies potential secondary accounts and can extract public SSH...
    Downloads: 3 This Week
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  • 4
    Albedo

    Albedo

    A recommender system for discovering GitHub repos

    ...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. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. ...
    Downloads: 0 This Week
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