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ATS using Neural Network

The project is simple Applicant Tracking System using a neural network without any high-level framework like TensorFlow or PyTorch. The system matches the keywords from Job description dictonaries to applicants' resume and predicts the job category with confidence score.

Features

Clean and preprocess raw resume text. Convert resumes to TF-IDF vectors (max 784 features) Predict job category from resumes using a multi-layer neural network Supports top-3 category suggestions with confidence levels Includes training functionality on custom labeled resumes

Installation

  1. Clone the repository

git clone https://github.com/hvrdhn/ATS.git
cd ATS
  1. Install dependencies

pip install -r requirements.txt

Files

  • "ATS.py" : Contains Neural Network class
  • "trainATS.py" : Data preprocessing, text extraction and training neural network.
  • "testATS.py" : loads the trained model and predicts job category with confidence score.

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