This project aims to build a time series forecasting model using PyTorch to predict future Bitcoin prices based on historical data. The model will utilize recurrent neural networks (RNNs) or transformers to capture temporal dependencies and make accurate predictions.
Dataset The dataset used for this project is the Bitcoin Historical Data. from Kaggle. It includes historical Bitcoin price data with features such as date, open price, close price, high price, low price, volume, and market cap. The dataset is available in CSV format and will be used for training and evaluation.