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Maximizing Neural Network Potential for Big Data Analytics: Leveraging Data-Driven Insights

EasyChair Preprint no. 12369

11 pagesDate: March 4, 2024

Abstract

Neural networks have emerged as powerful tools for analyzing large datasets in the realm of big data analytics. This paper explores the potential of neural networks in extracting valuable insights from vast and complex datasets, leveraging data-driven approaches to enhance decision-making processes. Through the utilization of sophisticated algorithms and deep learning techniques, neural networks can effectively process massive amounts of data to uncover patterns, trends, and correlations that may not be apparent through traditional analytical methods. This investigation aims to maximize the potential of neural networks in big data analytics by emphasizing the importance of leveraging data-driven insights to drive informed decision-making and achieve actionable outcomes.

Keyphrases: Big Data Analytics, Data-driven insights, decision making, deep learning, neural networks, pattern recognition, trend analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:12369,
  author = {William Jack},
  title = {Maximizing Neural Network Potential for Big Data Analytics: Leveraging Data-Driven Insights},
  howpublished = {EasyChair Preprint no. 12369},

  year = {EasyChair, 2024}}
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