My stock analysis project using LSTM and SARIMA. This is a test project and it is not financial advise.
AGPL-3.0 License
This project aims to predict the stock price of Apple Inc. (AAPL) using data from Yahoo Finance via the Rapid API. The prediction models are based on SARIMA (Seasonal Autoregressive Integrated Moving Average) and LSTM (Long Short-Term Memory) implemented using TensorFlow. The project also utilizes Grafana for data visualization, PostgreSQL for data storage, FastAPI for REST endpoints, and Docker for containerization.
This is just a sample analysis and it is not financial analysis for Apple Inc or any stock. I've tested out both SARIMA and LSTM for this project and have stored the weights of LSTM
git clone https://github.com/AbhijithGanesh/StockSage.git
POSTGRES_USER=''
POSTGRES_PASSWORD=''
POSTGRES_DB=''
DB_HOST=''
RAPID_API_KEY=''
pip install -r requirements.txt
docker compose up
uvicorn app:app
Data Fetching:
Data Storage:
Data Visualization:
REST Endpoint:
Machine Learning Models:
Containerization:
This project is licensed under the GPL. Feel free to re-use it😉