TensorFlow in Deep learning
Author(s):
Mrs.A.Pavithra, Mr.S.Murukanantha Prakash
ISSN:
2349-6002
Cite This Article:
TensorFlow in Deep learningInternational Journal of Innovative Research in Technology(www.ijirt.org) ,ISSN: 2349-6002 ,Volume 5 ,Issue 9 ,Page(s):142-147 ,January 2019 ,Available :IJIRT147525_PAPER.pdf
Keywords:
Deep Learning, TensorFlow, LeNet, AlexNet, ResNet, Logistic Regression
Abstract
Deep learning has revolutionized the technology industry. Modern machine translation, search engines, and computer assistants are all powered by deep learning. TensorFlow is used to do all its complex work very simple. TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. This trend will only continue as deep learning expands its reach into robotics, pharmaceuticals, energy, and all other fields of contemporary technology. It is rapidly becoming essential for the modern software professional to develop a working knowledge of the principles of deep learning.
Article Details
Unique Paper ID: 147525

Publication Volume & Issue: Volume 5, Issue 9

Page(s): 142 - 147
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