2 projects for "pyscripter python 2" with 2 filters applied:

  • Award-Winning Medical Office Software Designed for Your Specialty Icon
    Award-Winning Medical Office Software Designed for Your Specialty

    Succeed and scale your practice with cloud-based, data-backed, AI-powered healthcare software.

    RXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
    Learn More
  • Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place. Icon
    Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place.

    For healthcare Providers and Facilities

    Incredable streamlines and simplifies the complex process of medical credentialing for hospitals and medical facilities, helping you save valuable time, reduce costs, and minimize risks. With Incredable, you can effortlessly manage all your healthcare providers and their credentials within a single, unified platform. Our state-of-the-art technology ensures top-notch data security, giving you peace of mind.
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  • 1
    SSH Teste
    SSH TESTE v0.1, foi desenvolvido para realizar teste em servidores SSH Free, a idéia e foco foram de apenas criação de uma aplicação destinada a console, porém resolvir fazer uma aplicação orientada a objeto, usando a biblioteca Tkinter do próprio Python. Incluir novas funcionalidade como realizar a verificação da pagina onde se encontra os banco de dados aberto e extração dos dados usando a biblioteca HTML Parser..
    Downloads: 0 This Week
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  • 2

    dAnalytics

    dAnalytics is a software made for education in discriminant analysis.

    dAnalytics is a software made for educational purposes to work with discriminant analysis. It's a very simple calculator over bi-dimensional populations. You input a file with two columns (one for each variable) and tryout different separations of populations (blue and red) and analyze it's efficiency by observing the eigen value result for the attempted separation. It also gives many information about the statistics both of the input and the separated populations. There's a documentation...
    Downloads: 0 This Week
    Last Update:
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