This project aims to scrape job postings from LinkedIn and provide job recommendations based on the scraped data. It uses various Natural Language Processing (NLP) techniques to process job descriptions and titles, ultimately suggesting jobs that best match a set of skills.
|-- config
| |-- config.json
|-- data
|-- notebooks
| |-- NLP_processing_job_description.ipynb
| |-- NLP_processing_job_title_first_view.ipynb
| |-- NLP_processing_job_title_transformer.ipynb
| |-- data_transformer.ipynb
| |-- linkedin_scraper.ipynb
| |-- transform_scraped_data.ipynb
|-- pages
| |-- 02_job_search.py
| |-- 03_Skills.py
| |-- 04_Trainer.py
|-- src
| |-- myModules
| |-- __init__.py
| |-- my_NLP.py
| |-- prep.py
| |-- scraper_ds.py
| |-- transformer.py
|-- .gitignore
|-- README.md
|-- app.py
|-- requirements.txt
- Clone the repository to your local machine.
- Navigate to the project directory.
- Run
pip install -r requirements.txt
to install the required packages. - Update the
config.json
file with your LinkedIn credentials and other settings. - Run
app.py
to launch the Streamlit application.
- pandas
- numpy
- streamlit
- spacy
- bs4
- requests
- matplotlib
- seaborn
For a full list of dependencies, see requirements.txt
.