BSc Final Year Project

Description

Developed predictive stock price ML models using historical financial data and sentiment analysis, incorporating advanced feature engineering and machine learning techniques. Implemented and compared regression models to evaluate the impact of sentiment data on predictive accuracy, utilising metrics like MAE and R² . Automated data preprocessing pipeline for stock and sentiment data integration, including web scraping, natural language processing, and time-series alignment. Technologies: Python, Scikit-learn, PyTorch, Selenium, BeautifulSoup, Matplotlib, Git

Features

  • Machine Learning – Implementation of a custom LSTM model architecture using PyTorch

Technologies

Python
Git
Jupyter

Links

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Images

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