Big Data Analytics and Machine Learning

Abstract

Big data analytics has made revolutionary breakthroughs in commerce, science, industry, and society. Facebook, Twitter, and LinkedIn are examples of companies in the social networking domain. The scientific and technological advancement in the field of data analytics has helped to economically extract value from very large volumes of a wide variety of data to empower people in their business and private lives. The big data uprising over the years have greatly transformed man’s work, thought, and decision-making. The X-factor for utilizing this to maximum hugely depends on the data extraction ability through data analytics. Machine learning is at its peak due to its ability to provide meaningful insights, predictions, and decisions of data, further highlighting some promising learning methods in recent studies, such as deep learning, representation learning, distributed and transfer learning, parallel learning, kernel-based learning, and active learning. Big data analytics helps in uncovering various market trends, correlations, hidden patterns, and customer preferences, which play an important role in helping organizations making conducive decisions. Machine learning helps in accelerating this process with the help of a plethora of decision-making algorithms. Fusion of both big data and machine learning can classify the incoming data and translate the data into insights for various business needs. This chapter focusses on how interconnection of big data and machine learning can be capable of overcoming various challenges currently faced. Furthermore, a foundation for researchers in providing encouragement for new innovative techniques based on the amalgamation of machine learning with big data is provided.