https://github.com/akunna1/np-evaluation
ATS+ code and file conversion code for Neptune Technologies' job application platform
https://github.com/akunna1/np-evaluation
applicant-tracking-system data-mining data-science nltk-library os python re
Last synced: about 2 months ago
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ATS+ code and file conversion code for Neptune Technologies' job application platform
- Host: GitHub
- URL: https://github.com/akunna1/np-evaluation
- Owner: akunna1
- Created: 2024-02-10T23:44:20.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-28T23:30:45.000Z (6 months ago)
- Last Synced: 2025-06-12T21:47:18.753Z (4 months ago)
- Topics: applicant-tracking-system, data-mining, data-science, nltk-library, os, python, re
- Language: Jupyter Notebook
- Homepage: https://akunnatechstudio.com/mining
- Size: 23.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🧠 NP-Evaluation — Neptune Technologies
This project is part of the **Neptune Technologies** job application platform developed by [Akunna Tech Studio](https://akunnatechstudio.com/mining). It includes both the Applicant Tracking System (ATS+) evaluation logic and a file conversion utility to prep documents for text-based analysis.
## 📌 Project Purpose
To evaluate and extract insights from applicant resumes and cover letters by:
* Converting `.doc`, `.docx`, and `.pdf` formats to `.txt`
* Analyzing the cleaned text using Python for keyword scoring, match rate, and ATS readiness
## 🛠️ Built With
* Python
* NLTK
* OS module
* RE (Regex)
## 🗂️ Project Structure
```
├── Evaluation_code.ipynb # Main evaluation logic (keyword scoring, ATS match, etc.)
├── Evaluation_file_conversion.ipynb # Converts uploaded resumes (.docx/.pdf) to plain .txt
```
## ⚙️ How It Works
1. **File Conversion:**
Run `Evaluation_file_conversion.ipynb` to batch convert resumes into clean `.txt` files suitable for parsing and analysis.
2. **ATS+ Evaluation:**
Run `Evaluation_code.ipynb` to:
* Extract key sections from the resume (Skills, Experience, etc.)
* Score relevance to job descriptions
* Identify gaps and strengths for candidate optimization
## 🔍 Keywords & Analysis
* Text mining
* Resume parsing
* Job-to-resume matching
* ATS (Applicant Tracking System) simulation
## 📝 Notes
* This is a standalone module and can be integrated into broader HR or ATS pipelines.
* For demo/testing, use sample resumes stored locally in the project folder.