If you are learning or researching Deep Learning in Big Data, you should read this excellent paper about deep learning in Big Data.
Usually, the Big Data means extremely huge large data sets that can be analyzed to detect useful patterns, trends through some techniques. Deep Learning is a powerful technique that can be used for data analysis so that we find abstract patterns in Big Data. When we apply Deep Learning to Big Data, we can get unknown and useful patterns that were impossible so far.
We can apply Deep Learning that is a tool for understanding higher abstract knowledge in most steps of Big Data area problems. But preferably it needs high volumes of data. If we want to become more successful in this competitive area, we need to find abstract patterns. The more pattern, the more success.
With the development of Deep Learning, artificial intelligence is getting more and smarter. There is a hypothesis in this regard, the more data, the more abstract knowledge. So a handy survey of Big Data, Deep Learning and its application in Big Data is necessary.
In this paper, you can see the authors provide a comprehensive survey about what is Big Data, comparing methods, its research problems, and trends. Then a survey of Deep Learning, its methods, comparison of frameworks, and algorithms is presented. And at last, application of Deep Learning in Big Data, its challenges, open research problems……
Published in: 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)