API and training files for StockSense android application
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Updated
Jul 10, 2024 - Jupyter Notebook
API and training files for StockSense android application
The purpose of this project is to predict stock prices using historical data and financial indicators with LSTM networks. It involves data extraction, cleaning, model training, and an interactive app for predictions. This tool aids financial analysts, portfolio managers, and investors in making informed decisions.
S&P 500 stock price prediction using Transformer model
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This project, part of a bachelor's module at HTW Berlin, implemented and verified the paper "Stock Price Predictions with LSTM Neural Networks and Twitter Sentiment," focusing on Apple's stock price prediction.
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