Deep Learning for Big Data Analytics

Deep learning is extremely popular among data scientists and analysts due to its proven accuracy in recognizing speech, image processing, and Big Data analytics. Data is growing at exponential rate due to sensor networks and communications. It is analyzed that 90% data was generated during last 2 years and data will be increased at this pace in forthcoming years also. Deep learning has become more significant as it can be used for large scale of unlabeled data. The increase in number of hidden nodes with the sheer size of data resists learning. Deep learning with new algorithmic approaches is able to learn large-scale unlabeled data with less feature engineering. Big Data can be better analyzed by deep learning. In this paper, the focus is on new algorithms and techniques of deep learning which can provide better accuracy for large-scale complex and unstructured data.

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Authors and Affiliations

  1. Punjabi University, Patiala, India Gourav Bathla & Himanshu Aggarwal
  2. Thapar University, Patiala, India Rinkle Rani
  1. Gourav Bathla