Spaces:
Sleeping
Sleeping
Update README.md
Browse files
README.md
CHANGED
|
@@ -15,7 +15,46 @@ hf_oauth_scopes:
|
|
| 15 |
---
|
| 16 |
|
| 17 |
# Resume Analyzer App
|
| 18 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 19 |
|
| 20 |
## 📜 License
|
| 21 |
**Your code** is licensed under the [MIT License](LICENSE).
|
|
|
|
| 15 |
---
|
| 16 |
|
| 17 |
# Resume Analyzer App
|
| 18 |
+
# Resume Analyzer App
|
| 19 |
+
|
| 20 |
+
## Overview
|
| 21 |
+
The **Resume Analyzer App** is a powerful tool designed to evaluate and rank resumes based on their fit for a specific job. Ideal for recruiters screening candidates or job seekers refining their applications, this app scores resumes out of 100 using a data-driven approach. By comparing resumes to a provided job description, it delivers actionable insights to identify the best candidates or improve resume quality.
|
| 22 |
+
|
| 23 |
+
## Key Features
|
| 24 |
+
- **Job-Specific Analysis**: Evaluates resumes by comparing them to a user-provided job description.
|
| 25 |
+
- **Scoring Parameters**:
|
| 26 |
+
- Relevance to Job
|
| 27 |
+
- Experience Quality
|
| 28 |
+
- Skills Match
|
| 29 |
+
- Education & Certifications
|
| 30 |
+
- Achievements & Impact
|
| 31 |
+
- Clarity & Professionalism
|
| 32 |
+
- Customization
|
| 33 |
+
- **Detailed Feedback**: Provides a total score and breakdown by parameter, highlighting strengths and areas for improvement.
|
| 34 |
+
- **Flexible Weighting**: Adjusts scoring weights based on job type (e.g., emphasizing skills for tech roles).
|
| 35 |
+
- **Tech-Powered**: Built with Python, leveraging NLP (spaCy/NLTK), PDF parsing (PyPDF2/pdfplumber), and regex for robust analysis.
|
| 36 |
+
|
| 37 |
+
## How It Works
|
| 38 |
+
1. **Input**: Upload a resume (PDF or text) and a job description.
|
| 39 |
+
2. **Analysis**: The app extracts text, processes it with NLP, and scores it across defined parameters.
|
| 40 |
+
3. **Output**: Get a total score (e.g., 82/100) and a detailed breakdown (e.g., Skills: 14/15, Experience: 18/20).
|
| 41 |
+
4. **Ranking**: Compare multiple resumes to find the best fit for the job.
|
| 42 |
+
|
| 43 |
+
## Use Cases
|
| 44 |
+
- **Recruiters**: Quickly filter top candidates for a role.
|
| 45 |
+
- **Job Seekers**: Optimize your resume for a specific job posting.
|
| 46 |
+
- **Educators**: Teach students how to tailor resumes with data-backed feedback.
|
| 47 |
+
|
| 48 |
+
## Example
|
| 49 |
+
**Software Engineer Role**:
|
| 50 |
+
Score: 85/100
|
| 51 |
+
Relevance: 18/20, Skills: 14/15, Experience: 16/20, Clarity: 9/10, Customization: 8/10
|
| 52 |
+
|
| 53 |
+
|
| 54 |
+
## Why Use It?
|
| 55 |
+
- Saves time by automating resume screening.
|
| 56 |
+
- Provides objective, job-specific evaluations.
|
| 57 |
+
- Adapts to any industry or role with flexible scoring.
|
| 58 |
|
| 59 |
## 📜 License
|
| 60 |
**Your code** is licensed under the [MIT License](LICENSE).
|