Showing 5 open source projects for "access data"

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  • Red Hat Ansible Automation Platform on Microsoft Azure Icon
    Red Hat Ansible Automation Platform on Microsoft Azure

    Red Hat Ansible Automation Platform on Azure allows you to quickly deploy, automate, and manage resources securely and at scale.

    Deploy Red Hat Ansible Automation Platform on Microsoft Azure for a strategic automation solution that allows you to orchestrate, govern and operationalize your Azure environment.
  • Gain insights and build data-powered applications Icon
    Gain insights and build data-powered applications

    Your unified business intelligence platform. Self-service. Governed. Embedded.

    Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
  • 1
    Gretel Synthetics

    Gretel Synthetics

    Synthetic data generators for structured and unstructured text

    .... Need to synthesize one or multiple data types? We have you covered. Even take advantage or multimodal data generation. Synthesize and transform multiple tables or entire relational databases. Mitigate GDPR and CCPA risks, and promote safe data access. Accelerate CI/CD workflows, performance testing, and staging. Augment AI training data, including minority classes and unique edge cases. Amaze prospects with personalized product experiences.
    Downloads: 1 This Week
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  • 2
    Copulas

    Copulas

    A library to model multivariate data using copulas

    Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D...
    Downloads: 0 This Week
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  • 3
    BlenderProc

    BlenderProc

    Blender pipeline for photorealistic training image generation

    A procedural Blender pipeline for photorealistic training image generation. BlenderProc has to be run inside the blender python environment, as only there we can access the blender API. Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance...
    Downloads: 1 This Week
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  • 4
    Mimesis

    Mimesis

    High-performance fake data generator for Python

    Mimesis is an open source high-performance fake data generator for Python, able to provide data for various purposes in various languages. It's currently the fastest fake data generator for Python, and supports many different data providers that can produce data related to people, food, transportation, internet and many more. Mimesis is really easy to use, with everything you need just an import away. Simply import an object, called a Provider, which represents the type of data you need...
    Downloads: 0 This Week
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  • Simplify Purchasing For Your Business Icon
    Simplify Purchasing For Your Business

    Manage what you buy and how you buy it with Order.co, so you have control over your time and money spent.

    Simplify every aspect of buying for your business in Order.co. From sourcing products to scaling purchasing across locations to automating your AP and approvals workstreams, Order.co is the platform of choice for growing businesses.
  • 5
    Tofu

    Tofu

    Tofu is a Python tool for generating synthetic UK Biobank data

    Tofu is a Python library for generating synthetic UK Biobank data. The UK Biobank is a large open-access prospective research cohort study of 500,000 middle-aged participants recruited in England, Scotland and Wales. The study has collected and continues to collect extensive phenotypic and genotypic detail about its participants, including data from questionnaires, physical measures, sample assays, accelerometry, multimodal imaging, genome-wide genotyping and longitudinal follow-up for a wide...
    Downloads: 0 This Week
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