Machine learning using Information and Communication Technologies.
DOI:
https://doi.org/10.64092/4x9fz791Keywords:
Learning, technology, automationAbstract
Over the years, technology has played a leading role worldwide, continuously evolving to meet human needs. This evolution has generated innovations that enhance learning capabilities by providing tools that allow problem-solving through the exploitation of technological opportunities. The objective of this study is to analyze the impact of machine learning on knowledge acquisition processes and the optimization of tasks through the use of Information and Communication Technologies (ICT). These systems enable near-instantaneous learning, as they are designed to facilitate access to and management of information. Machine learning was developed to adapt to task execution based on models that generate new solutions through technological innovation. In this way, the capacity to produce advances capable of automatically responding to the demands of the information society is increased. Currently, it is observed that companies and organizations continuously update their systems to improve performance, enabling applications to operate autonomously based on the data collected. Consequently, new technologies aim to promote continuous improvement for the benefit of humans and the digital environment.
Downloads
References
Automation Anywhere, Inc. (2023). ¿Qué es el RPA? Automatización robótica de procesos. Automation Anywhere. https://www.automationanywhere.com/la/rpa/robotic-process-automation
BBVA. (2019). Te contamos qué es el 'machine learning' y cómo funciona. BBVA. https://www.bbva.com/es/innovacion/machine-learning-que-es-y-como-funciona/
Google Cloud. (2023). ¿Qué es el aprendizaje automático? https://cloud.google.com/learn/what-is-machine-learning?hl=es-419#section-2
Iberdrola, S. A: (2022). ¿Qué es un chatbot y para qué sirve? https://www.iberdrola.com/innovacion/que-es-un-chatbot
Innova Advanced Consulting. (2020). Previsión de ventas: qué es y cómo hacerla. Innova Advanced Consulting. https://www.innovaconsulting.es/blog/prevision-de-ventas/
Microsoft Corporation. (2023). ¿Qué es el aprendizaje automático? https://azure.microsoft.com/es-mx/resources/cloud-computing-dictionary/what-is-machine-learning-platform
Quijano, V. (2021). ¿Qué es el índice de deserción de clientes y cómo evitarlo? https://victorquijano.com/blog/que-es-el-indice-de-desercion-de-clientes-y-como-evitarlo/
Thomos, N., Maugey, T., & Toni, L. (2022). Machine Learning for Multimedia Communications. Sensors (Basel, Switzerland), 22(3), 819. https://doi.org/10.3390/s22030819
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Nelly Mayved Jandette-Castillo, Evelyn Sayuri Ruiz-Maturano (Autor/a)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors who publish in Sophia Research Review (SRR), agree to the following terms:
1. Copyright
Authors retain unrestricted copyright to their work. Authors grant the journal the right of first publication. To this end, they assign the journal non-exclusive exploitation rights (reproduction, distribution, public communication, and transformation). Authors may enter into additional agreements for the non-exclusive distribution of the version of the work published in the journal, provided that acknowledgment of its initial publication in this journal is given.
© The authors.
2. License
The articles are published in the journal under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). The terms can be found at: https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
This license allows:
- Sharing: Copying and redistributing the material in any medium or format.
- Adapting: Remixing, transforming, and building upon the material.
Under the following terms:
- Attribution: You must give appropriate credit, provide a link to the license, and indicate if any changes were made. You may do this in any reasonable manner, but not in any way that suggests the licensor endorses or sponsors your use.
- NonCommercial: You may not use the material for commercial purposes.
- ShareAlike: If you remix, transform, or build upon the material, you must distribute your creation under the same license as the original work.
There are no additional restrictions. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
