Layered Approximation for Deep Neural Networks
Published: 2019
Author(s) Name: Utpal Chakraborty |
Author(s) Affiliation: Chief Data Scientist, Head of Artificial Intelligence, Yes Bank, Mumbai, Maharashtra, India.
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Abstract
Artificial Intelligence has created immense hype in the last decade and the credit for the same goes to the groundbreaking
breakthrough named “Deep Learning” or “Deep Neural Network”. Although “Artificial Neural Network”, the foundation of Deep
Learning as a concept has been prevalent since 1958 but the actual implementation for solving real business use cases have only
been possible over the last decade. Deep Neural Networks has demonstrated significant results in the fields of computer vision,
speech recognition, and machine translation, and outperformed human brain in many instances. Artificial Neural Network, as it
is inspired from human biological neural superstructure has few structural similarities but not possible in terms of how the human
brain or biological neural network works because we have still limited information on its functioning. Nevertheless, Deep Neural
Network paved the way for many possibilities and currently it is the most promising technology that we have in the field of Artificial
Intelligence.
Keywords: Deep Neural Network, Artificial Intelligence, Artificial Neural Network, Layered Approximation
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