Big Data Meets Machine Learning: Strategies for Efficient Data Processing and Analysis in Large Datasets
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Abstract
In recent years, the proliferation of big data has transformed various sectors, necessitating the development of advanced techniques for efficient data processing and analysis. This paper explores the intersection of big data and machine learning, highlighting strategies to handle vast datasets effectively. We discuss various machine learning algorithms tailored for big data environments, emphasizing scalability, performance optimization, and resource management. Additionally, we investigate data preprocessing methods, feature selection, and model evaluation metrics to enhance the accuracy of machine learning models. The findings underscore the importance of integrating big data technologies with machine learning approaches to unlock valuable insights and drive decision-making processes in data-intensive applications.
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