Leveraging Machine Learning Algorithms for Predictive Analytics in Big Data: Challenges and Opportunities

Shengyuan Zhang

Artificial Intelligence and Digital Technology, 2024, vol. 1, issue 1, 42-49

Abstract: This article explores the integration of machine learning with Big Data for predictive analytics, highlighting its potential and challenges. It provides an overview of key machine learning algorithms, such as decision trees, random forests, and neural networks, and discusses their application in Big Data environments. The article examines challenges such as data quality, model interpretability, and ethical concerns surrounding data privacy. Furthermore, emerging technologies like quantum computing and Edge AI are introduced as future trends that could revolutionize predictive analytics. The article also presents case studies from healthcare and finance, showcasing real-world applications of predictive analytics. In conclusion, the article emphasizes the importance of responsible data management and the significant role machine learning will continue to play in driving innovation across industries.

Keywords: big data; quantum computing; edge AI; data privacy; decision trees; neural networks; healthcare; finance (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:axf:icssaa:v:1:y:2024:i:1:p:42-49

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