Machine Learning Algorithms, models and Applications: A Review

Review Article

Authors

  • Suleiman Saadon Fawzy Department of Computer center, I.T, Al-Mustansiriyah University, Baghdad, Iraq
  • Nada Hassan Jasem College of Science, University of Baghdad, Baghdad, Iraq

DOI:

https://doi.org/10.31695/IJERAT.2020.3607

Keywords:

Supervised Learning, Un-Supervised Learning, Machine Learning, Support Vector Machine

Abstract

Machine Learning (ML) can be defined as unfolding from AI, also it is specified as a field related to the computer sciences. Also, ML is specified as one of the multi-disciplinary fields, a combination related to the statistics as well as the algorithms of computer sciences that has been majorly utilized in classification and predictive analyses. The other section of this study concentrating on the impact related to major ML algorithms and approaches. Furthermore, the presented study will specify different ML tools required to run the projects of ML. The major concern related to the work has been studying the major methods as well as the case studies related to utilizing ML with regard to forecasting in various areas like supply chain demand, tourism demand forecasting, stock price forecasting, solar irradiation forecasting as well as consideration related to ML and NN approaches.

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How to Cite

Suleiman Saadon Fawzy, & Nada Hassan Jasem. (2020). Machine Learning Algorithms, models and Applications: A Review: Review Article. International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) DOI: 10.31695/IJERAT, 6(8), 29–37. https://doi.org/10.31695/IJERAT.2020.3607

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