nlp_news

The project's aim is to use Natural Language Processing (NLP) to perform sentiment analysis on news articles and pass that as a feature to predict exchange traded fund (ETF) prices.

News archive: https://components.one/datasets/all-the-news-2-news-articles-dataset/
News website: https://inshorts.com/en/read/business
Stock price: https://www.sharesmagazine.co.uk/shares/share/VEVE/historic-prices

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

The Python version used is 3.7.1 and it is recommended to create a virtual environment and install the required packages:

#cd to root directory
python -m venv venv
source venv/Scripts/activate
pip install -r requirements.txt

Next, pre-commit is used to run black, mypy check and nbstripout before committing to Git. The .pre-commit-config.yaml file is included in the repo so only the following step is required after installing the pre-commit package (which is included in the requirements.txt):

pre-commit install 

To use the virtual environment in notebook, you have to install ipykernel package first (which is also included in the requirements.txt). Then, you need to add your virtual environment to Jupyter:

python -m ipykernel install --user --name=venv

Deployment

To deploy project on a live system