A Comprehensive Study on the Role of Artificial Intelligence in Advancing Machine Learning Algorithms for Intelligent Automation, Pattern Recognition, and Scalable Data Analysis
Keywords:
Artificial intelligence, Machine learning, Intelligent automation, Pattern recognition, Scalable data analysisAbstract
Content of the Abstract:
This paper explores how artificial intelligence (AI) has influenced and advanced machine learning (ML) algorithms, focusing on intelligent automation, pattern recognition, and scalable data analysis.
Purpose:
To synthesize knowledge from foundational research to show AI’s role in enhancing traditional ML approaches and enabling new capabilities.
Design/methodology/approach:
A review of classic and influential research papers in AI and ML before 2015, with thematic analysis of applications, challenges, and developments.
Findings:
AI-driven ML approaches such as representation learning, automated feature extraction, and scalable algorithm design markedly improved performance across domains.
Practical implications:
Insights can guide researchers and practitioners in selecting and designing AI-empowered ML systems for automation and data-driven decision-making.
Originality/value:
This paper consolidates seminal work on AI/ML integration and provides an organized perspective on its applications in intelligent systems.
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