🚀 Passionate about building scalable AI systems, data-driven applications, and real-world problem-solving solutions.
- 💡 Interested in Machine Learning, Deep Learning & AI Systems
- ⚙️ Strong focus on end-to-end system design
- 📊 Love working on data-driven applications
- 🌱 Currently exploring LLMs, Distributed Systems & Cloud
Languages
- Python
- JavaScript
Frameworks & Tools
- Scikit-learn
- Pandas, NumPy, PostgreSQL, Docker
AI / ML
- Machine Learning (Regression, Random Forest, XGBoost)
- Deep Learning (LSTM, Neural Networks)
- NLP & Sentiment Analysis
- Recommendation Systems
- RAG (Retrieval-Augmented Generation)
- Combines ML + DL (LSTM) models
- Uses SHAP for explainability
- Focus on real-world production readiness
- Modular architecture:
- Candidate Generator
- Similarity Calculator
- Ranking System
- Supports collaborative & content-based filtering
- Flask-based microservice
- Real-time feedback loop
- SQLite + caching for performance
- AI-powered multi-language code understanding system
- Uses LLM pipeline for semantic merging
- Supports Python, JavaScript, Java, Go
- Collects data from app stores
- Performs sentiment analysis
- Detects bugs & feature requests automatically
- Retrieves old content using vector DB
- Rewrites content using LLM
- Evaluates using BLEU scoring
- Parses and analyzes resumes
- Extracts key insights for hiring decisions
Give a ⭐ to the repositories and feel free to collaborate!