Showing 4 open source projects for "dataset"

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  • 1
    Kaggle CLI

    Kaggle CLI

    The official CLI to interact with Kaggle

    Kaggle CLI is Kaggle’s official command-line interface for interacting with the Kaggle platform from a terminal. It lets users authenticate, search resources, download files, submit competition entries, manage datasets, work with models, run notebooks, and read discussion content without relying only on the web interface. The tool is useful for data scientists who want to automate Kaggle workflows inside scripts, CI jobs, notebooks, or reproducible local environments. It supports both...
    Downloads: 2 This Week
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  • 2
    Data Contract CLI

    Data Contract CLI

    Enforce Data Contracts

    ...It uses YAML-based contract files to define the structure, meaning, quality rules, service levels, and connection details for a data product. The tool can connect to real data sources and check whether the actual dataset matches the schema, constraints, and quality expectations described in the contract. It supports both the Data Contract Specification and the Open Data Contract Standard, making it useful for teams standardizing data governance across different platforms. It can run locally, inside CI/CD pipelines, through Docker, or directly from Python code. ...
    Downloads: 1 This Week
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  • 3

    NGSbinningpytools

    Python tools for binning NGS scaffolds to various genomes.

    ...Now, it is possible to sequence all organisms present in a metagenomic community. However, a critical problem is to determine the host organism for each genomic fragment present in the dataset. This project provides the computational tools for assigning the organismal identity for each genomic scaffold in the given dataset. For more detailed documentation please refer to the link below: https://sourceforge.net/p/ngsscaffolds/wiki/Documentation/
    Downloads: 0 This Week
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  • 4
    Malware Classifier

    Malware Classifier

    Perform quick, easy classification of binaries for malware analysis.

    ...Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a dataset of approximately 100,000 malicious programs and 16,000 clean programs. The tool extracts seven key features from an unknown binary, feeds them to one of the four classifiers or all of them, and presents its classification of the unknown binary.
    Downloads: 1 This Week
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