@article{3511,
  keywords = {Forex, Machine Learning, Micro Services, Reduction Model, Software Architecture, Support Vector Machine},
  author = {Kevin Gordillo-Orjuela and Paulo Alonso Gaona-García and Carlos Enrique Montenegro-Marín},
  title = {Design of a Machine Learning-Based Platform for Currency Market Prediction: A Fundamental Design Model},
  abstract = {Prediction models in foreign exchange markets have been very popular in recent years, and in particular, through the use of techniques based on Machine Learning. This growth has made it possible to train several techniques that increasingly allow us to improve predictions according to the criteria that each algorithm supports and can cover. However, the development of these models and their deployment within computer platforms is a complex task, given the variety of approaches that each researcher uses based on the training process and therefore by definition of the model, which leads to the consumption of high computing resources for its training, as well as various processes for its deployment. For this reason, the following article focuses on designing a technological platform oriented to micro services, which minimizes the consumption of resources and facilitates the integration of various techniques and the analysis of various criteria, which improves their analysis and validation in a Web environment.},
  year = {9998},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {In press},
  chapter = {1},
  number = {In press},
  pages = {1-11},
  month = {11/2024},
  issn = {1989-1660},
  url = {https://www.ijimai.org/journal/bibcite/reference/3511},
  doi = {10.9781/ijimai.2024.11.002},
}