https://github.com/cytronicoder/stock-data-visualiser
💹 Doing some data analysis using historical data from NASDAQ
https://github.com/cytronicoder/stock-data-visualiser
flask machine-learning stock-market
Last synced: 2 months ago
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💹 Doing some data analysis using historical data from NASDAQ
- Host: GitHub
- URL: https://github.com/cytronicoder/stock-data-visualiser
- Owner: cytronicoder
- License: mit
- Created: 2022-10-22T06:13:04.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-11-29T17:26:50.000Z (over 1 year ago)
- Last Synced: 2025-01-02T04:29:37.726Z (over 1 year ago)
- Topics: flask, machine-learning, stock-market
- Language: Jupyter Notebook
- Homepage:
- Size: 292 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
### 🚀 I will be working on this experiment again during summer 2023... stay tuned!
# Stock Data Visualiser
This is a simple stock data visualiser that uses the [Alpha Vantage API](https://www.alphavantage.co/documentation/) to get stock data. I built this to learn more about data crunching and visualisation. The aim of this project is to build a fully functional LSTM model that predicts future stock prices based on historical prices using PyTorch. It is currently in development, and I will be adding more features as I learn more about data visualisation.
## Installation
To install the required packages, run the following command:
```bash
pip install -r requirements.txt
```
## Usage
You can either run the program using the command line, or by using the Jupyter Notebook (locally or on Google Colab - recommended).
### Command Line
To run the program using the command line, run the following command:
```bash
python lstm-model/train.py
```
**Experimental: I am currently developing a web app to pair with this project.** You can run the web app using the following command:
```bash
cd client
yarn install
yarn run dev
```
## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate. If you have any questions, feel free to open an issue. I will try to respond as soon as possible.