A review of machine learning applications in big data

Big data analytics is one high focus of data science and there is no doubt that big data is now quickly growing in all science and engineering fields. Big data analytics is the process of examining and analyzing massive and varied data that can help organi-zations make more-informed business decisions, especially for uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information. Big data has become essential as numerous organizations deal with massive amounts of specific information, which can contain useful information about problems such as national intelligence, cybersecurity, biology, fraud detection, marketing, astronomy, and medical informatics. Several promising machine learning techniques can be used for big data ana-lytics including representation learning, deep learning, distributed and parallel learning, transfer learning, active learning, and kernel-based learning. In addition, big data analytics demands new and sophisticated algorithms based on machine learning techniques to treat data in real-time with high accuracy and productivity.

Keywords:

MachineLearning , bigdata , Analyzing the data