7 Role of Machine Learning in Big Data

Machine learning is promising when large-scale data processing is considered as it has the capability of learning from the previous data and incorporating those findings on new incoming data. Although its applications in big data are limitless, it faces a vast number of challenges. This paper gives us an introduction to the implementation of machine learning in big data. We discuss about four out of the five Vs of big data and about the challenges faced in this regard. Some previous works are also discussed in the related work section. Some of the tools under batch analysis, stream analysis, and interactive analysis are explained here. Under the section of machine learning algorithms in big data, popular algorithms in supervised, semi-supervised, and unsupervised categories are briefly discussed. Machine learning also finds its way in sectors like healthcare, financial services, automotive, etc. It can also be used in chatbots, recommendation engines, user modeling, predictive analytics, etc. Then come the challenges that are faced by the machine learning algorithms. Under each characteristic, there come several areas that are a challenge and can be improved to enhance the productivity of the algorithm. Large and complex datasets are also difficult to process. New techniques need to be evolved or the existing technologies need to be updated for enhanced processing and better results.