Resume_screnning

Project: Resume Screnning App using Streamlit

Install

This project requires Python and the following Python libraries installed:

• NumPy
• Pandas
• matplotlib
• scikit-learn
• NLTK

You must also install software to run and execute a Google Colab.

Code

Template code is provided in the Resume_Screening.ipynb notebook file. You will also be required to use the included app.py Python file for the streamlit app and the resume-dataset.csv dataset file to complete your work.

Run

In a terminal or command window, navigate to the top-level project directory resume-screening/ (that contains this README) and run one of the following commands:

ipython notebook Resume_Screening.ipynb

or

jupyter notebook Resume_Screening.ipynb

or open with Juoyter Lab

jupyter lab

This will open the Jupyter Notebook software and project file in your browser.

Data

Dataset used: https://www.kaggle.com/datasets/gauravduttakiit/resume-dataset

Features

• Good Predictor: After Screening the Resume, the app predicts the category to be placed according to the skills mentioned in the resume.
• Simple UI: A simple UI provides a good experience.

Screenshot: