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Cryptocurrency Price Prediction Using TPU-Based Distributed Machine Learning

Cryptocurrency Price Prediction Using TPU-Based Distributed Machine Learning

Yokesh Babu Sundaresan, Mohd Hammad Khan, Devdutt Sharma, Anbarasi Masilamani, Sukriti Jaitly, Mohak Verma
Copyright: © 2022 |Pages: 21
ISBN13: 9781799892748|ISBN10: 1799892743|EISBN13: 9781799892762
DOI: 10.4018/978-1-7998-9274-8.ch004
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MLA

Sundaresan, Yokesh Babu, et al. "Cryptocurrency Price Prediction Using TPU-Based Distributed Machine Learning." Blockchain Technologies for Sustainable Development in Smart Cities, edited by P. Swarnalatha and S. Prabu, IGI Global, 2022, pp. 44-64. https://doi.org/10.4018/978-1-7998-9274-8.ch004

APA

Sundaresan, Y. B., Khan, M. H., Sharma, D., Masilamani, A., Jaitly, S., & Verma, M. (2022). Cryptocurrency Price Prediction Using TPU-Based Distributed Machine Learning. In P. Swarnalatha & S. Prabu (Eds.), Blockchain Technologies for Sustainable Development in Smart Cities (pp. 44-64). IGI Global. https://doi.org/10.4018/978-1-7998-9274-8.ch004

Chicago

Sundaresan, Yokesh Babu, et al. "Cryptocurrency Price Prediction Using TPU-Based Distributed Machine Learning." In Blockchain Technologies for Sustainable Development in Smart Cities, edited by P. Swarnalatha and S. Prabu, 44-64. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-9274-8.ch004

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Abstract

The development of blockchain has led to the emergence and widespread use of decentralized cryptocurrencies around the globe. As of 2021, the global market capitalization of cryptocurrencies has crossed two trillion dollars. With increasing popularity and adoption, investors have begun to see cryptocurrencies as an alternative to conventional financial assets. However, the volatility associated with cryptocurrencies makes them a highly risky investment. This gives rise to the need for accurate and efficient price prediction models which can help reduce risks associated with cryptocurrency investments. The model aims at predicting the price of two popular cryptocurrencies: Bitcoin and Ethereum. Tensor processing unit (TPU) is used for providing a distributed environment for the proposed model. The results show that the distributed TPU-trained model performed significantly better than the conventional CPU-trained model in terms of training time while maintaining a high degree of accuracy.

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