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  Published Paper Details:

  Paper Title

COMPASSION BETWEEN VARIOUS OPTIMIZATION TECHNIQUES USED IN MACHINE LEANING

  Authors

  Rohit Garg,  Sohit Aggarwal

  Keywords

:- Artificial Intelligence, Optimization Algorithms, Adam, Nestrov, Gradient Descent

  Abstract


Optimization in simplest terms optimization is choosing inputs that will result in the best possible outputs or making things the best that they can be. In the era from 2006 to 2009 peoples are looking to improve learning algorithms. At that time the best learning algorithm was gradient descent and the researchers are looking for a better learning algorithm than gradient descent. The researchers are looking for a better solution to the initialization problem in a neural network or some clear wait configuration. And that time they have sigmoid as a nonlinear activation function and they are searching for some better activation function. So they have started to invent new optimization techniques to improve all above parameters. Here in this paper we are comparing some latest Optimisation algorithms and made the conclusion that which algorithm is better in artificial intelligence e applications.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2105951

  Paper ID - 207814

  Page Number(s) - i846-i848

  Pubished in - Volume 9 | Issue 5 | May 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Rohit Garg,  Sohit Aggarwal,   "COMPASSION BETWEEN VARIOUS OPTIMIZATION TECHNIQUES USED IN MACHINE LEANING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 5, pp.i846-i848, May 2021, Available at :http://www.ijcrt.org/papers/IJCRT2105951.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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