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    Online Resource
    Online Resource
    Inventive Research Organization ; 2021
    In:  Journal of Soft Computing Paradigm Vol. 3, No. 3 ( 2021-9-20), p. 205-217
    In: Journal of Soft Computing Paradigm, Inventive Research Organization, Vol. 3, No. 3 ( 2021-9-20), p. 205-217
    Abstract: In recent years, there has been an increase in demand for machine learning and AI-assisted trading. To extract abnormal profits from the bitcoin market, the machine learning and artificial intelligence (AI) assisted trading process has been used. Each day, the data gets saved for the specified amount of time. These approaches produce great results when integrated with cutting-edge algorithms. The results of algorithms and architectural structures drive the development of cryptocurrency market. The unprecedented increase in market capitalization has enabled the cryptocurrency to flourish in 2017. Currently, the market accommodates totally 1500 cryptocurrencies, all of which are actively trading. It is always possible to mine the cryptocurrency and use it to pay for online purchases. The proposed research study is more focused on leveraging the accurate forecast of bitcoin prices via the normalization of a particular dataset. With the use of LSTM machine learning, this dataset has been trained to deploy a more accurate forecast of the bitcoin price. Furthermore, this research work has evaluated different machine learning methods and found that the suggested work delivers better results. Based on the resultant findings, the accuracy, recall, precision, and sensitivity of the test has been calculated.
    Type of Medium: Online Resource
    ISSN: 2582-2640
    URL: Issue
    URL: Issue
    Language: English
    Publisher: Inventive Research Organization
    Publication Date: 2021
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