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  Published Paper Details:

  Paper Title

CRYPTOCURRENCY PRICE ANALYSIS USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE

  Authors

  Deepali A Patil,  Tanmay A Jain,  Mohamed Azeem R Khot,  Bhargav D Joshi

  Keywords

Long Short Term Memory, Recurrent Neural Network, Cryptocurrency, Machine Learning

  Abstract


The role of Cryptocurrency has been really important in reshaping the financial system due to its increasing popular appeal and worldwide acceptance. A lot of people have started to make investments in Cryptocurrency, but the dynamical features, uncertainty, and predictability of Cryptocurrency are still mostly unknown, which dramatically risks the investments. It is a matter of trying to understand the factors that influence the value formation. In this study, we use advanced artificial intelligence frameworks of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) to predict the price of different cryptocurrencies. Evaluation of these algorithms is carried out to determine better prediction to analyze the price dynamics of different cryptocurrencies including Bitcoin, Ethereum, and Ripple. However, the explanation of the predictability could vary depending on the design of the machine-learning model which is implemented.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2106763

  Paper ID - 209360

  Page Number(s) - g422-g424

  Pubished in - Volume 9 | Issue 6 | June 2021

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.39367

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

  E-ISSN Number - 2320-2882

  Cite this article

  Deepali A Patil,  Tanmay A Jain,  Mohamed Azeem R Khot,  Bhargav D Joshi,   "CRYPTOCURRENCY PRICE ANALYSIS USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 6, pp.g422-g424, June 2021, Available at :http://www.ijcrt.org/papers/IJCRT2106763.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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