🤖 ML-Powered Resume Analyzer

Intelligent Resume Classification & Analysis using Machine Learning and NLP

Automatically classify resumes into job categories, extract meaningful insights, and provide actionable improvement suggestions using Natural Language Processing (NLP), TF-IDF, Sentence Transformers, and Machine Learning.

---

📖 Table of Contents

• Overview
• Features
• Demo Workflow
• Project Architecture
• Machine Learning Pipeline
• Tech Stack
• Folder Structure
• Installation
• Dataset
• Usage
• Configuration
• Model Details
• Resume Advice Engine
• Future Improvements
• Contributing
• License
• Author

---

📌 Overview

Recruiters receive hundreds of resumes every day.

Manually sorting them into suitable job categories is time-consuming and inconsistent.

This project automates that process using Natural Language Processing (NLP) and Machine Learning.

The system:

• Converts resumes into readable text
• Cleans and preprocesses the content
• Extracts textual features
• Classifies resumes into job domains
• Generates personalized improvement suggestions

Everything runs locally, making the project privacy-friendly since resumes never leave your machine.

---

✨ Features

✅ Resume PDF to Text Conversion

✅ CSV Resume Dataset Processing

✅ Text Cleaning & NLP Preprocessing

✅ TF-IDF Feature Extraction

✅ Logistic Regression Classifier

✅ Sentence Transformer Embeddings

✅ Resume Category Prediction

✅ Resume Quality Analysis

✅ Keyword Suggestions

✅ Missing Section Detection

✅ CLI-Based Workflow

✅ YAML Configuration Support

---

🎯 Demo Workflow

                Resume
                   │
                   ▼
          PDF / CSV Conversion
                   │
                   ▼
          Text Preprocessing
                   │
                   ▼
          Feature Extraction
         (TF-IDF / Embeddings)
                   │
                   ▼
      Machine Learning Classifier
                   │
                   ▼
     Resume Category Prediction
                   │
                   ▼
        Resume Advice Generator

---

🏗 Project Architecture

                 +-------------------+
                 |   Resume Dataset  |
                 +---------+---------+
                           |
                           ▼
                  Resume Converter
                           |
                           ▼
                 Text Preprocessing
                           |
                           ▼
               Feature Engineering
          +-----------------------------+
          | TF-IDF | SentenceTransformer |
          +-----------------------------+
                           |
                           ▼
              Logistic Regression Model
                           |
                           ▼
                  Resume Prediction
                           |
                           ▼
                 Resume Advice Engine

---

🧠 Machine Learning Pipeline

1. Data Collection

Training Dataset:

• Updated Resume Dataset (CSV)

Testing Dataset:

• Resume PDFs

---

2. Data Cleaning

The preprocessing stage performs:

• Lowercase conversion
• URL removal
• HTML tag removal
• Special character removal
• Stopword removal
• Whitespace normalization

---

3. Feature Engineering

TF-IDF

Converts textual information into numerical vectors while preserving important word frequencies.

Sentence Transformers

Uses pre-trained embeddings for richer semantic understanding of resume content.

Current embedding model:

all-MiniLM-L6-v2

---

4. Classification

Current baseline model:

• Logistic Regression

Future planned models:

• SVM
• Random Forest
• XGBoost
• LightGBM
• Neural Networks

---

💻 Tech Stack

Programming

• Python

Machine Learning

• Scikit-learn
• Sentence Transformers

NLP

• NLTK
• Regular Expressions

Data Processing

• Pandas
• NumPy

File Handling

• PyPDF2
• PDFPlumber

Configuration

• YAML

---

Example output plot:

---

📂 Folder Structure

ML-powered_resume_analyser/

│
├── data/
│   ├── raw/
│   ├── processed/
│   ├── test/
│
├── models/
│
├── src/
│   ├── convert_dataset.py
│   ├── convert_test_data.py
│   ├── train_classifier.py
│   ├── predict.py
│   ├── advice.py
│
├── assets/
│
├── config.yaml
├── requirements.txt
└── README.md

---

⚙ Installation

Clone Repository

git clone https://github.com/yourusername/ML-powered_resume_analyser.git

cd ML-powered_resume_analyser

---

Create Virtual Environment

Windows

python -m venv .venv

.venv\Scripts\activate

macOS/Linux

python3 -m venv .venv

source .venv/bin/activate

---

Install Dependencies

pip install -r requirements.txt

Compatibility Fix

pip install numpy==1.26.0 --force-reinstall

---

📊 Dataset

Training Dataset

UpdatedResumeDataSet.csv

Testing

Resume PDFs

Recommended structure

data/

raw/
processed/
test/

---

🚀 Usage

Convert CSV Dataset

python src/convert_dataset.py \
--csv data/raw/UpdatedResumeDataSet.csv \
--outdir data/processed/converted

---

Convert Resume PDFs

python src/convert_test_data.py \
--pdfdir data/test \
--outdir data/processed/converted_test

---

Train Model

python src/train_classifier.py

---

Predict Resume Category

python src/predict.py --input resume.txt

---

Generate Resume Advice

python src/advice.py --input resume.txt

---

⚙ Configuration

model:

  embedding: all-MiniLM-L6-v2

  tfidf_max_features: 1000

  advice_threshold: 0.5

---

📈 Model Details

Component	Algorithm
Feature Extraction	TF-IDF
Embeddings	Sentence Transformers
Classifier	Logistic Regression
Language	English
Prediction	Resume Category

---

💡 Resume Advice Engine

The advice module currently evaluates:

• Resume Length
• Missing Keywords
• Missing Sections
• Soft Skills
• Resume Structure
• Role Match
• Improvement Suggestions

Example Output

Predicted Category

→ Data Scientist

Suggestions

✔ Add Projects section

✔ Include SQL keyword

✔ Mention TensorFlow experience

✔ Improve resume summary

✔ Add measurable achievements

---

📸 Screenshots

Add screenshots here after running the project.

Example:

assets/

home.png

prediction.png

advice.png

training.png

Then include

![Prediction](assets/prediction.png)

![Advice](assets/advice.png)

---

📊 Future Improvements

• Web Interface using Flask
• Streamlit Dashboard
• Deep Learning Classifier
• Resume Ranking
• Skill Extraction
• ATS Score Prediction
• GPT-powered Resume Feedback
• Docker Support
• REST API
• Multi-language Resume Support

---

🤝 Contributing

Contributions are welcome.

To contribute:

1. Fork the repository

2. Create a new branch

git checkout -b feature-name

3. Commit changes

git commit -m "Added feature"

4. Push

git push origin feature-name

5. Open a Pull Request

---

📄 License

This project is licensed under the MIT License.

---

👨‍💻 Author

Ruthvik Sharma

AI & Machine Learning Engineer

GitHub: https://github.com/ruthviksharma-d

LinkedIn: https://linkedin.com/in/ruthvik-sharma

---

⭐ If you found this project useful, consider giving it a star!