Resume Checker

The Resume Checker is a web-based application built in Python using Streamlit. It serves as a tool for screening resumes, utilizing Natural Language Processing (NLP) techniques and machine learning models to analyze and categorize resume content.

Table of Contents

Introduction

Features

Installation

Usage

Dependencies

Contributing

Introduction

The hiring process often involves sifting through numerous resumes to identify suitable candidates. The Resume Checker automates this process by providing a platform to upload resumes and receive predictions about the most relevant job category for each candidate. This application is particularly useful for recruiters and hiring managers who need to efficiently evaluate large volumes of resumes.

Features

Upload resumes in various formats including PDF, TXT, and DOCX.

Clean resume text to remove irrelevant information and standardize the format.

Utilize TF-IDF vectorization to convert resume text into numerical features.

Apply a trained machine learning model to predict the most suitable job category for each resume.

Display predictions along with confidence scores to assist in decision-making.

User-friendly interface with responsive design for seamless user experience.

Installation

Clone the repository:

git clone https://github.com/your_username/resume-checker.git

cd resume-checker

Usage

To run the application, execute the following command:

streamlit run app.py

This will start the Streamlit server, and you can access the application through your web browser.

Dependencies

Streamlit

Pickle

NLTK

Regular Expressions (re)

Contributing Contributions to the Resume Checker project are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.