ML Engineer · NLP · Python Developer
Building end-to-end ML systems — from raw data to working demos. Currently focused on NLP pipelines, text classification, and GenAI applications.
Context-aware travel assistant for weather, festivals, and local tips.
- Built a Python CLI tool surfacing real-time weather data + curated regional travel info
- Structured around clean separation of data fetching, formatting, and CLI presentation
- Stack: Python · REST APIs ·
argparse/click·requests
Text classification pipeline with model evaluation and explainability.
- Trained and evaluated multiple classifiers (Logistic Regression, fine-tuned transformers) on news datasets
- Implemented precision/recall/F1 evaluation loop; compared baseline vs. transformer approaches
- Stack: Python · scikit-learn · HuggingFace Transformers · Pandas · NLTK
Projects, skills, and contact — built and deployed independently.
| Area | Focus |
|---|---|
| ML Fundamentals | Model evaluation, bias-variance, cross-validation |
| NLP | Tokenization, embeddings, transformer architectures |
| MLOps (next) | Model serving, experiment tracking (MLflow) |
- Beginner-to-intermediate NLP / text classification projects
- Python CLI tools or small developer utilities
- End-to-end ML projects: data → model → demo
If you're building something in this space, open an issue or reach out directly.
