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@article{181448,
        author = {Preeti Bisen and Ankita Tiwari and Nitya Khare},
        title = {A Comparative Review of Machine Learning Approaches for Bitcoin Price Prediction: Bridging the  Gap with Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {4015-4017},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=181448},
        abstract = {The volatile nature of cryptocurrency markets, especially Bitcoin, has driven significant research interest in developing predictive models using Machine Learning (ML) and Deep Learning (DL). This review paper examines the application of ML algorithms such as Linear Regression and Random Forest in forecasting Bitcoin prices. Despite their simplicity and interpretability, these models often fall short in capturing the complex temporal dependencies and nonlinear dynamics of cryptocurrency data. We propose a hybrid Deep Learning-based approach to improve prediction accuracy and present a future direction for research in this field.},
        keywords = {Bitcoin, Machine Learning, Linear Regression, Random Forest, Cryptocurrency Forecasting, Deep Learning, Time Series Prediction},
        month = {June},
        }