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Empirical Insights on Cloud Services for Machine Learning Applications

Author

Listed:
  • Adrian MICU

    (Dunarea de Jos University of Galati, Romania)

  • Marius GERU

    (Transilvania University of Brasov, Romania)

  • Angela-Eliza MICU

    (Ovidius University of Constanta, Romania)

  • Alexandru CAPATINA

    (Dunarea de Jos University of Galati, Romania)

  • Constantin AVRAM

    (Dunarea de Jos University of Galati, Romania)

  • Robert RUSU

    (Dunarea de Jos University of Galati, Romania)

Abstract

As the volume of data increases, becomes more complex and valuable, people's limited capabilities present real challenges in deciphering and interpreting an increasingly unpredictable economic environment. In essence, Machine Learning is the artifact of artificial intelligence generated and shared mainly by the technological environment, where almost any information can be documented, measured and stored digitally, thus becoming data that can be processed to generate actionable information reusable in multiple spheres. of activity. The aim of this research is a comparative analysis of the main cloud services available for Machine Learning algorithms. The research results offer a dynamic vision to the researchers involved in the FutureWeb project, who are looking for the most efficient cloud platforms for the services offered by the AI Media platform.

Suggested Citation

  • Adrian MICU & Marius GERU & Angela-Eliza MICU & Alexandru CAPATINA & Constantin AVRAM & Robert RUSU, 2020. "Empirical Insights on Cloud Services for Machine Learning Applications," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 85-90.
    • Handle: RePEc:ddj:fseeai:y:2020:i:2:p:85-90
    DOI: https://doi.org/10.35219/eai15840409110
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