Solutions to Critical issues on Big Data Using Machine Learning Techniques

  • S. Umadevi , T.Chandrakala , B.Bavani , S.Leena Nesamani , TM.Ezhilmathi

Abstract

Nowadays big data have been used tremendously in all areas of computer engineering. The
main advantage of big data is that the user is able to analyze huge data and can refer different
possible opportunities. Initially traditional machine learning methods like supervised learning,
unsupervised learning and reinforcement learning are used. But the traditional techniques are
not able to cope up with massive amount of data ,also in traditional technique the data collected
are stored in a centralized unit which will be very difficult as the amount of data grew bigger.
To overcome this advanced machine learning techniques like Representation learning, Deep
Learning, Distributed and parallel learning, Transfer learning and Active Learning are
proposed. These learning techniques also have certain critical issues like huge scale data
learning, Different data categories learning. High speed continuous data learning and mining
valuable data learning. Various problems and their solutions to these issues are discussed below

Published
2020-05-01
How to Cite
S. Umadevi , T.Chandrakala , B.Bavani , S.Leena Nesamani , TM.Ezhilmathi. (2020). Solutions to Critical issues on Big Data Using Machine Learning Techniques. International Journal of Advanced Science and Technology, 29(7s), 3054-3059. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/17381