| TensorFlow in Deep learning |
|---|
| Author(s): |
| Mrs.A.Pavithra, Mr.S.Murukanantha Prakash |
| ISSN: |
| 2349-6002 |
| Cite This Article: |
TensorFlow in Deep learning, International 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 |
| Article Preview & Download |
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