This project analyses Bitcoin's price movements leading up to the anticipated 2024 halving event. It encompasses various steps, including data collection, preprocessing, exploratory data analysis (EDA), model selection, training, evaluation, predictive analysis, fine-tuning, monitoring and updating.
If you find this project useful, kindly consider giving it a star ⭐ on GitHub. Contributions are also welcome!
This project focuses on analysing Bitcoin's price trends and movements as we approach the 2024 halving event. By leveraging historical data and advanced modeling techniques, we aim to provide insights into potential price behaviors and market trends.
- Data Collection: Gathering historical Bitcoin price data and relevant market indicators.
- Data Preprocessing: Cleaning and preparing the data for analysis.
- Exploratory Data Analysis (EDA): Visualising and understanding the data patterns and trends.
- Model Selection: Choosing appropriate models for analysis based on the data characteristics.
- Model Training: Training selected models on the preprocessed data.
- Model Evaluation: Assessing the performance of models using various metrics.
- Predictive Analysis: Making predictions based on the trained models.
- Fine-Tuning: Adjusting model parameters to improve accuracy and performance.
- Monitoring and Updating: Continuously monitoring model performance and updating as needed.
Contributions are welcome! Feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.
For any inquiries or suggestions, please contact Nafisa Lawal Idris.