Revolutionising Predictive Analytics: A machine learning and AI perspective in cloud-based data science

This paper dissects the revolution machine learning (ML) and artificial intelligence (AI) have brought to using predictive analytics in cloud computing for data science. The study also outlines today’s developments in both ML and AI. It evaluates the stochastic probabilities of the challenges and opportunities, considering the courses of action available for boosting the prediction analysis. The article covers areas such as the use of ML and AI in practice, real-life examples and examples of practical application, and nowadays and in future, attachments that reflect the real-life application and effectiveness of the methods in predictive analytics. The research uses qualitative and quantitative approaches to assess AI-based solutions and suggests guidelines for developing an effective and innovative digital environment.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-30
DOI
https://doi.org/10.5281/zenodo.15266580
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
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article

Revolutionising Predictive Analytics: A machine learning and AI perspective in cloud-based data science

Zenodo (CERN European Organization for Nuclear Research)
Explainable Artificial Intelligence (XAI)
article

Revolutionising Predictive Analytics: A machine learning and AI perspective in cloud-based data science

article en

Abstract

This paper dissects the revolution machine learning (ML) and artificial intelligence (AI) have brought to using predictive analytics in cloud computing for data science. The study also outlines today’s developments in both ML and AI. It evaluates the stochastic probabilities of the challenges and opportunities, considering the courses of action available for boosting the prediction analysis. The article covers areas such as the use of ML and AI in practice, real-life examples and examples of practical application, and nowadays and in future, attachments that reflect the real-life application and effectiveness of the methods in predictive analytics. The research uses qualitative and quantitative approaches to assess AI-based solutions and suggests guidelines for developing an effective and innovative digital environment.

Zenodo (CERN European Organization for Nuclear Research)
University of Staffordshire (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 67%
Explainable Artificial Intelligence (XAI)
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