• Arraram Arshith Kumar
• Yeleti Nandhu Reddy
• Rasa Sai Teja
• P.Sruthi
• K.Sudhakar Reddy

Introducing Our Prediction for Bitcoin Prices Utilizing machine learning (ML), a machine learning model that is applied with specific algorithms to infer the price of Bitcoin given further information about the variables influencing the direction of the price. Because Indian law enforcement is allowing tax deductions for earnings made from bitcoin investments and returns, bitcoin's popularity has just peaked again. Bitcoin is a payment method and digital asset that is used as virtual money on the Internet. Due to its ability to facilitate anonymous payments between individuals, it is a favored payment method for illicit activities conducted online. Because of its recent price increase, Bitcoin has drawn lots of interest from the public and media. This research aims to ascertain the Bitcoin price's predictable price direction. We should be able to gain the knowledge we need to understand cryptocurrency's future via machine learning models. Although it can't predict the future, it can indicate the overall trend and direction in which prices are likely to move. The suggested approach aims to create a machine learning model in which the dataset's patterns are discovered through data analysis, and the machine learning algorithm is then utilized to forecast the price of bitcoin based on the biases that have a direct impact on it. We were able to approach the improved version of the Bitcoin price prediction model thanks to the insightful comments from the domain experts.

Bitcoin Price Prediction, Logistic Regression, ARIMA, SVM, Machine Learning, support vector machine

"Bitcoin Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d91-d97, April-2024, Available :http://www.jetir.org/papers/JETIR2404314.pdf

"Bitcoin Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd91-d97, April-2024, Available at : http://www.jetir.org/papers/JETIR2404314.pdf