Predicting bitcoin prices: A machine learning approach for accurate forecasting
Rishabh Jain, Shekhar Srivastava, Prakhar Shukla · 2025
This project investigates the active realm of Bitcoin price forecasting through the glass of machine intelligence models, including Logistic Regression, Support Vector Machines (SVM), and XGBoost Classifier. Leveraging a different dataset including historical and actual-occasion Bitcoin price dossier, the study employs an orderly method for dossier collection, feature collection, model preparation, and judgment. The aim is to embellish the veracity of short-term and unending forecasts, making the challenges posed apiece explosive cryptocurrency retail. The project extends further hypothetical exploration, climactic in the incident of a convenient web connect. This connects employs HTML, CSS, and Flask API to provide authentic-opportunity forecasts, extending the gap betwixt leading predictive models and proficient uses.