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This is a web application built using Streamlit for screening resumes. The application classifies resumes into various categories using a pre-trained machine learning model.

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rajput999/Resume-Screening-WebApp

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Resume Screening App

This is a web application built using Streamlit for screening resumes. The application classifies resumes into various categories using a pre-trained machine learning model.

You can access the live application here.

Installation

  1. Clone the repository or download the source code.
  2. Navigate to the project directory.
cd /path/to/project
  1. Install the required packages.
pip install -r requirements.txt

Usage

  1. Upload a resume file (in .txt or .pdf format) using the web interface.
  2. The application will predict the category of the resume and display it.

Model Training (Optional)

If you want to train the model yourself, follow these steps:

  1. Load your dataset and preprocess it as shown in the train_model.py script.

  2. Train the model and save the trained models (clf.pkl and tfidf.pkl).

  3. Ensure the trained models are in the project directory before running the Streamlit application.

Files

  • app.py: Main Streamlit application script.
  • train_model.py: Script to train and save the machine learning model.
  • requirements.txt: List of required Python packages.
  • README.md: This file.

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This is a web application built using Streamlit for screening resumes. The application classifies resumes into various categories using a pre-trained machine learning model.

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