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.
python
machine-learning
jupyter-notebook
data-visualization
stock-price-prediction
data-extraction
predictive-modeling
data-cleaning
long-short-term-memory
time-series-forecasting
financial-data-analysis
investment-decision
streamlit
-
Updated
Jul 10, 2024 - Jupyter Notebook