Deep Machine Learning and Neural Networks: An Overview

Received Feb 10, 2017 Revised Apr 14, 2017 Accepted May 23, 2017 Deep learning is a technique of machine learning in artificial intelligence area. Deep learning in a refined "machine learning" algorithm that far surpasses a considerable lot of its forerunners in its capacities to perceive syllables and picture. Deep learning is as of now a greatly dynamic examination territory in machine learning and example acknowledgment society. It has increased colossal triumphs in an expansive zone of utilizations, for example, speech recognition, computer vision and natural language processing and numerous industry item. Neural network is used to implement the machine learning or to design intelligent machines. In this paper brief introduction to all machine learning paradigm and application area of deep machine learning and different types of neural networks with applications is discussed. Keyword:

[1]  Guoqiang Peter Zhang,et al.  Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[2]  Grenville J. Armitage,et al.  A survey of techniques for internet traffic classification using machine learning , 2008, IEEE Communications Surveys & Tutorials.

[3]  Daizhan Cheng,et al.  State–Space Analysis of Boolean Networks , 2010, IEEE Transactions on Neural Networks.

[4]  Pascal Vincent,et al.  Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Xue-wen Chen,et al.  Big Data Deep Learning: Challenges and Perspectives , 2014, IEEE Access.

[6]  Sudharman K. Jayaweera,et al.  A Survey on Machine-Learning Techniques in Cognitive Radios , 2013, IEEE Communications Surveys & Tutorials.

[7]  Wei-Jen Lee,et al.  Neural network based demand forecasting in a deregulated environment , 1999 .

[8]  Xiao Li,et al.  Machine Learning Paradigms for Speech Recognition: An Overview , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[9]  Wei-Yang Lin,et al.  Machine Learning in Financial Crisis Prediction: A Survey , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[10]  Sankar K. Pal,et al.  Web mining in soft computing framework: relevance, state of the art and future directions , 2002, IEEE Trans. Neural Networks.

[11]  S. Mitra,et al.  Bioinformatics with soft computing , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).