🎓 B.Tech in Artificial Intelligence & Machine Learning
💻 Full-Stack Python Developer | Machine Learning | NLP
🚀 Passionate about building end-to-end ML-powered web applications
📈 Focused on real-world, deployable systems, not just models

• Developing full-stack ML applications (Frontend + Backend + ML)
• Integrating Machine Learning models with RESTful APIs
• Building React-based frontends for ML systems
• Designing scalable backend services for inference & data flow
• Preparing for ML Engineer / Python Backend / Full-Stack roles

Tech: Python, Pandas, Scikit-learn, Flask, REST APIs, HTML, CSS

• Built a regression-based ML system to predict student scores
• Designed Flask backend endpoints for ML inference
• Created a clean web UI for real-time predictions
• Deployed as a complete ML-powered web application

🔗 Live Demo: https://student-performance-ai-p30z.onrender.com

Tech: Python, Random Forest, Flask, REST APIs, HTML, CSS

• Classified students into Low / Medium / High risk categories
• Implemented feature importance for explainability
• Built backend inference logic with frontend integration
• Designed path-safe project structure for easy deployment

Tech: Python, NLP (TF-IDF), Logistic Regression, Flask, REST APIs

• Built an NLP pipeline to classify feedback as Positive / Neutral / Negative
• Improved negation handling using bigram TF-IDF features
• Addressed class imbalance with class-weighted learning
• Combined multiple feedback text fields using Git feature branching
• Built a multi-input web interface aligned with training logic
• Documented model limitations and experimentation strategy

• Python
• JavaScript
• HTML5, CSS3

• React (component-based UI, hooks fundamentals)
• Responsive UI design
• State & form handling
• Frontend–backend integration
• API consumption (fetch / axios)

• Flask (routing, forms, REST APIs)
• RESTful API design principles
• Model inference endpoints
• Request validation & error handling
• Backend–ML integration
• Basic deployment concepts (Gunicorn)

• Scikit-learn
• Pandas, NumPy
• Regression & Classification models
• NLP (TF-IDF, Logistic Regression)
• Model evaluation & explainability

• MongoDB Atlas
• Git & GitHub (branching, version control)
• VS Code

📧 Email: basudevd983@gmail.com
💼 LinkedIn: https://www.linkedin.com/in/basudev-das

💡 Focused on building scalable, ML-driven web systems using modern frontend and backend engineering practices.