Scalable Machine Learning Techniques for Efficient Analysis of Big Data: Advancements, Challenges, and Future Directions

Dr. Sudesh Rani

Abstract: With the exponential growth of big data, there is an increasing need for scalable machine learning (ML) techniques that can efficiently analyze massive datasets. This paper presents a comprehensive review of the advancements, challenges, and future directions in the domain of scalable machine learning for big data analytics. We explore the state-of-the-art techniques and methodologies developed to address the unique requirements and complexities of big data analysis.

Keywords: Big data analytics, machine learning, scalability, distributed computing, online learning, ensemble methods, dimensionality reduction, data preprocessing