2 projects for "python data analysis" with 2 filters applied:

  • SoftCo: Enterprise Invoice and P2P Automation Software Icon
    SoftCo: Enterprise Invoice and P2P Automation Software

    For companies that process over 20,000 invoices per year

    SoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
    Learn More
  • 1
    Hiper

    Hiper

    A statistical analysis tool for performance testing

    Hiper is an open-source command-line tool designed for statistical analysis of web performance and page load behavior during performance testing. The tool repeatedly loads a specified webpage multiple times and gathers detailed timing metrics in order to produce more reliable performance measurements than single-run benchmarks. By averaging data across multiple page loads, Hiper helps developers understand whether performance optimizations actually improve real-world page loading behavior. ...
    Downloads: 0 This Week
    Last Update:
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  • 2

    Java/C Comparative Benchmarks

    Java and C Comparative Performance Benchmarks

    A collection of software benchmarks developed to compare the performance of Java with C on identical code. No language libraries were used to avoid implementation differences. Some of the benchmarks are also implemented in Python and Scala. There are benchmarks for bit twiddling, numerical computing, data structure manipulation, concurrent computing, callouts to native libraries, and, graphics processing units (GPU) utilization.
    Downloads: 0 This Week
    Last Update:
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