Big Data Analytics and Implementation Challenges of Machine Learning in Big data
The efficiency of machine learning and deep learning in a sensitive environment was evaluated in this paper, which reviewed security problems in big data.
Abstract
The term "big data" refers to an information processing system that combines different conventional data techniques. Big data also includes a large amount of personally identifiable and authenticated data, making privacy a major concern. Various techniques have been developed to provide security and efficient data processing. Machine learning is a form of data technology that deals with one of the most important and least understood aspects of the data collected. Deep learning algorithms, similar to machine learning algorithms, learn programmers automatically from data and are thought to improve the efficiency and security of large data sets. The efficiency of machine learning and deep learning in a sensitive environment was evaluated in this paper, which reviewed security problems in big data. This paper begins by providing an overview of machine learning and deep learning algorithms. The research then moves on to machine learning problems and challenges, as well as potential solutions. The investigation into deep learning principles of big data continues after that. Finally, the report examines approaches used in recent research developments and concludes with recommendations for the future.