【文件属性】：
文件名称：深度学习在大数据应用上
文件大小：1.67MB
文件格式：PDF
更新时间：2022-04-21 15:55:54
论文
Deep learning, as one of the most currently remarkable machine learning techniques, has achieved great success
in many applications such as image analysis, speech recognition and text understanding. It uses supervised and
unsupervised strategies to learn multi-level representations and features in hierarchical architectures for the
tasks of classification and pattern recognition. Recent development in sensor networks and communication
technologies has enabled the collection of big data. Although big data provides great opportunities for a broad of
areas including e-commerce, industrial control and smart medical, it poses many challenging issues on data
mining and information processing due to its characteristics of large volume, large variety, large velocity and
large veracity. In the past few years, deep learning has played an important role in big data analytic solutions. In
this paper, we review the emerging researches of deep learning models for big data feature learning.
Furthermore, we point out the remaining challenges of big data deep learning and discuss the future topics