A Deep Insight into Deep Learning Architectures, Algorithms and Applications

Abstract

The current scenario expresses that deep learning is the leading technology in the field of machine learning. Deep learning is a form of artificial intelligence that effectively uses neural network concepts where the computing system is essentially a multi-layered mesh architecture, which is motivated by the human brain and nervous system. The multiple hidden layers of CNN extract higher level features from large datasets and its methodology are speedily becoming a best choice for every field. Deep learning methods have improved and are highly developed in object recognition, Natural Language Processing, classification of images, medical image analysis etc. This paper provides introduction of different deep learning architectures, algorithms and the optimization methods used to improve the accuracy and performance of the deep learning model. And also, described challenges, obstacles to be faced while training a deep learning model and introduced applications of deep learning in various fields.