Smart Resume Analyzer 📄✨

Streamlining recruitment through intelligent resume analysis

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📋 Table of Contents

Overview
Key Features
Technology Stack
Architecture
Installation
Usage
Screenshots
Future Roadmap
Contributing
License
Acknowledgments

🔍 Overview

Smart Resume Analyzer is an intelligent web application that leverages Natural Language Processing (NLP) to automate the resume screening process. By analyzing resumes against job descriptions, the system provides objective, data-driven insights to help recruiters identify the most suitable candidates efficiently.

✨ Key Features

Intelligent Resume Parsing

Extracts and categorizes information from PDF resumes
Identifies education, experience, and skills automatically
Processes multiple resumes simultaneously

Advanced Matching Algorithm

Matches resumes against job requirements using weighted criteria
Distinguishes between required and preferred skills
Employs semantic similarity for context-aware matching

Interactive Visualizations

Skill category radar charts
Color-coded skill gap analysis
Progress indicators for match scores

Customizable Analysis

Adjustable weights for different matching criteria
Interactive sliders for personalized assessment

Comprehensive Reporting

Downloadable PDF reports
Detailed candidate information and match scores
Visual representations of strengths and skill gaps

🛠️ Technology Stack

Frontend	• HTML5, CSS3, JavaScript • Responsive design with custom styling • Interactive elements for file uploads and parameter adjustment
Backend	• Python 3.8+ • Flask web framework • RESTful API endpoints
NLP & Data Processing	• NLTK for tokenization and lemmatization • spaCy for entity recognition and semantic analysis • PyPDF2 for document parsing
Data Visualization	• Matplotlib for chart generation • Base64 encoding for web display
Reporting	• FPDF for PDF generation

🏗️ Architecture

Smart Resume Analyzer implements a modular architecture:

+---------------------+
|  User Interface     |
|  (Web Frontend)     |
+----------+----------+
           |
           v
+----------+----------+
|  Web Application    |
|  (Flask Server)     |
+----------+----------+
           |
   +-------+-------+
   |       |       |
   v       v       v
+-----+ +-----+ +-----+
|File | |NLP  | |Match|
|Proc.| |Proc.| |Eng. |
+-----+ +-----+ +-----+
   |       |       |
   +-------+-------+
           |
           v
+----------+----------+
| Visualization &     |
| Reporting Engine    |
+----------+----------+

⚙️ Installation

Prerequisites

Python 3.8 or higher
pip package manager
Virtual environment (recommended)

Setup Process

Clone the repository:

git clone https://github.com/hassanrrraza/resume_analyzer
cd resume_analyzer

Create and activate a virtual environment:
```
python -m venv .venv
```

# On Windows .venv\Scripts\activate

# On macOS/Linux source .venv/bin/activate


3. Install dependencies:
   ```bash
   pip install -r requirements.txt

Download required NLP models:

python -m spacy download en_core_web_md
python -m nltk.downloader punkt stopwords wordnet averaged_perceptron_tagger

Run the application:
```
python main.py
```
Access the application at http://localhost:5000

🚀 Usage

Resume Analysis Process

Upload Resumes
- Drag and drop PDF files
- Or click to browse and select files
- Multiple files can be uploaded simultaneously
Enter Job Description
- Paste job posting text
- Include required and preferred skills sections for best results
Customize Weights (Optional)
- Adjust importance of required skills (default: 60%)
- Adjust importance of preferred skills (default: 20%)
- Adjust importance of semantic similarity (default: 20%)
View Results
- Overall match scores
- Skills breakdown by category
- Education and experience details
- Skill gap analysis
Download Reports
- Generate comprehensive PDF summary
- Share with team members or stakeholders