Showing 2 open source projects for "analytics"

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  • Cloud tools for web scraping and data extraction Icon
    Cloud tools for web scraping and data extraction

    Deploy pre-built tools that crawl websites, extract structured data, and feed your applications. Reliable web data without maintaining scrapers.

    Automate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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  • Skillfully - The future of skills based hiring Icon
    Skillfully - The future of skills based hiring

    Realistic Workplace Simulations that Show Applicant Skills in Action

    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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    NYC Taxi Data

    NYC Taxi Data

    Import public NYC taxi and for-hire vehicle (Uber, Lyft)

    ...It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities.
    Downloads: 1 This Week
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  • 2
    Reproducible-research

    Reproducible-research

    A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.

    In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility....
    Downloads: 0 This Week
    Last Update:
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