A study of distributed and Scalable ML Techniques to Big Data: Challenges and advancements

Abstract

With the exponential growth of large data, scalable machine learning (ML) is the increasing requirement of techniques that can efficiently analyze the dataset. This paper presents a comprehensive review of progression, challenges and future instructions in the domain of scalable machine learning for Big data analytics. We detect state -of -the -art techniques and functioning developed to address the unique requirements and complexities of large data analysis.