Harnessing the Power of ML/AI: Transforming Data into Actionable Insights

Artificial intelligence (AI) and machine learning (ML) have become game-changing technologies transforming how businesses glean insights from massive amounts of data. This in-depth article examines the core ideas, practical applications, and implementation techniques of ML/AI in various industries. The article discusses the crucial elements of strategic implementation, such as problem identification, data preparation, and model development lifecycles, while examining the progress of machine learning methodologies from supervised and unsupervised to deep learning. It delves further into the key instruments and technologies advancing machine learning, emphasizing the value of strong frameworks and effective data processing infrastructure. The article illustrates the observable effects of ML/AI deployment with thorough case studies from the retail, financial services, and healthcare industries. The article's conclusion examines new developments in explainable AI, edge AI, federated learning, and autoML, offering predictions for their future.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-01-22
DOI
https://doi.org/10.30574/ijsra.2025.14.1.0111
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Harnessing the Power of ML/AI: Transforming Data into Actionable Insights

Suman Ankampally
International Journal of Science and Research Archive
Scientific Computing and Data Management
article

Harnessing the Power of ML/AI: Transforming Data into Actionable Insights

Suman Ankampally
article en

Abstract

Artificial intelligence (AI) and machine learning (ML) have become game-changing technologies transforming how businesses glean insights from massive amounts of data. This in-depth article examines the core ideas, practical applications, and implementation techniques of ML/AI in various industries. The article discusses the crucial elements of strategic implementation, such as problem identification, data preparation, and model development lifecycles, while examining the progress of machine learning methodologies from supervised and unsupervised to deep learning. It delves further into the key instruments and technologies advancing machine learning, emphasizing the value of strong frameworks and effective data processing infrastructure. The article illustrates the observable effects of ML/AI deployment with thorough case studies from the retail, financial services, and healthcare industries. The article's conclusion examines new developments in explainable AI, edge AI, federated learning, and autoML, offering predictions for their future.

International Journal of Science and Research ArchiveVol. 14(1)
Openalex Percentile: Top 99%
Scientific Computing and Data Management
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