Forecasting data for cryptocurrency using streamlit web app.
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Updated
May 31, 2021 - Jupyter Notebook
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cryptocurrency-price-forecasting
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This repository implements an XGBoost model for predicting the prices of financial instruments, such as stocks and cryptocurrencies. Using gradient boosting techniques, it aims to capture patterns in price movements, enhancing prediction accuracy across various datasets.
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Updated
Dec 22, 2024 - Python
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