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@article{168934,
        author = {Ankita Soni and Dr. Sachin Patel},
        title = {A Data Driven Machine Learning Model for Predicting Crypto Currency Prices},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {2371-2376},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168934},
        abstract = {Data driven machine learning models have been extensively used for forecasting crypto prices, which is typically challenging due to the random and volatile nature of crypto prices. In addition, businesses that rely on crypto price predictions for financial research and investments stand to lose a lot of money if even a little estimate is off.  In recent times, methods based on artificial intelligence and machine learning have gained popularity for predicting cryptocurrency prices. This is because these methods outperform traditional statistical methods. To forecast cryptocurrency prices, the suggested study uses a scaled-back propagation technique based on steepest descent in conjunction with data pre-processing utilizing the discrete wavelet transform (DWT). It has been demonstrated that the suggested method achieves a lower mean square percentage error than the previously used method.},
        keywords = {Data Analytics, Crypto Currencies, Bitcoin Prices, Deep Neural Networks, Forecasting Error.},
        month = {October},
        }