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High-Dimensional Data Processing: Benchmarking Machine Learning and Deep Learning Architectures in Local and Distributed Environments

Distributed, Parallel, and Cluster Computing 2025-12-12 v1 Artificial Intelligence

Abstract

This document reports the sequence of practices and methodologies implemented during the Big Data course. It details the workflow beginning with the processing of the Epsilon dataset through group and individual strategies, followed by text analysis and classification with RestMex and movie feature analysis with IMDb. Finally, it describes the technical implementation of a distributed computing cluster with Apache Spark on Linux using Scala.

Keywords

Cite

@article{arxiv.2512.10312,
  title  = {High-Dimensional Data Processing: Benchmarking Machine Learning and Deep Learning Architectures in Local and Distributed Environments},
  author = {Julian Rodriguez and Piotr Lopez and Emiliano Lerma and Rafael Medrano and Jacobo Hernandez},
  journal= {arXiv preprint arXiv:2512.10312},
  year   = {2025}
}

Comments

8 pages, 3 figures

R2 v1 2026-07-01T08:19:59.237Z