Exploring the Synergy Between Machine Learning and Big Data: A Comprehensive Survey of Algorithms and Applications

Abstract

In the contemporary era of technology-driven advancements, the synergy between Machine Learning (ML) and Big Data has emerged as a transformative force, revolutionizing industries and reshaping the way we extract knowledge from vast datasets. This comprehensive survey delves into the heart of this synergy, aiming to provide a thorough understanding of its key facets, applications, challenges, and future prospects. Our survey begins by elucidating the foundational concepts of both Machine Learning and Big Data, establishing a solid framework for the ensuing exploration. We traverse the landscape of ML algorithms specially tailored to tackle the challenges posed by Big Data, unveiling their strengths and weaknesses through real-world case studies across diverse domains. A focal point of our research lies in the revelation of how the integration of Machine Learning with Big Data leads to groundbreaking advancements. We examine how this partnership fuels predictive analytics, anomaly detection, and personalized recommendations, ultimately enhancing decision-making processes, user experiences, and operational efficiency. Yet, this synergy is not without its hurdles. Ethical considerations, data privacy, and computational scalability emerge as critical challenges that must be addressed as this partnership matures. Our survey sheds light on these issues, emphasizing the need for responsible and transparent data practices.