🚀 AI-Powered Resume Analyzer & Career Recommendation System
An intelligent full-stack web application that analyzes resumes using Machine Learning and recommends the most suitable job roles based on extracted skills. The system also provides skill insights and scoring to help users understand their career alignment.
📌 Overview This project is designed to assist job seekers by: Analyzing resume content Extracting relevant skills Predicting the most suitable job role Providing structured output with insights
🧠 How It Works The system follows this pipeline: User enters or uploads resume content Text is processed and cleaned TF-IDF vectorization is applied Trained Machine Learning model predicts job role Result is displayed on a structured result page
🔄 System Flow User Input → Flask Backend → TF-IDF Vectorizer → ML Model → Role Prediction → Result Display
🛠️ Tech Stack Frontend HTML CSS JavaScript Backend Python Flask Machine Learning Scikit-learn TF-IDF Vectorizer Logistic Regression
✨ Key Features 🔍 Resume skill extraction 🤖 Machine Learning-based job role prediction 📊 Structured result output 🌐 Clean and responsive UI 🧩 Modular project structure
🚀 Installation & Setup 1️⃣ Clone the Repository git clone https://github.com/yourusername/your-repo-name.git cd your-repo-name 2️⃣ Create Virtual Environment (Recommended) python -m venv venv venv\Scripts\activate (Windows) 3️⃣ Install Dependencies pip install -r requirements.txt 4️⃣ Run the Application python app.py Open your browser and visit: http://127.0.0.1:5000/
🌍 Deployment The application can be deployed using platforms like: Render Railway PythonAnywhere
📈 Future Enhancements Resume file upload (PDF parsing) Skill gap analysis with recommendations Role-based scoring visualization Admin analytics dashboard Integration with job listings API
🎯 Learning Outcomes Through this project, the following concepts were implemented: Natural Language Processing Text Vectorization (TF-IDF) Supervised Machine Learning Model Serialization using Pickle Flask-based full-stack development Deployment-ready application structure
👨💻 Author Rakshith Reddy Engineering Student | Machine Learning & Full Stack Development Enthusiast