Final-year Computer Science student at Matrusri Engineering College, Hyderabad (CGPA: 7.9), actively seeking Data Science / ML Engineering roles from June 2026.
I build end-to-end ML pipelines — from raw data and model training to REST API deployment and frontend integration. My work spans NLP, computer vision, and recommendation systems. I care about understanding why a model works, not just that it does.
"RoBERTa scored 99.9% — and that's exactly why I didn't trust it."
Languages
Python JavaScript SQL HTML CSS
ML / Data
Scikit-learn Pandas NumPy
Frameworks
Flask FastAPI React
Databases
MongoDB PostgreSQL
Tools
Git GitHub VS Code Jupyter Notebook
Core CS
DSA OOP OS DBMS Computer Networks
NLP · RoBERTa · Naive Bayes · Flask · React · 2026
Built an ensemble combining Multinomial Naive Bayes + TF-IDF (84.8% accuracy) with a fine-tuned RoBERTa (99.9% in-distribution), achieving a 97.1% F1 score on the WELFake dataset (72,134 articles).
Key finding: RoBERTa's near-perfect score reflects stylistic overfitting, not semantic understanding — which is precisely what motivated the hybrid design. Deployed with a Flask REST backend and React frontend serving real-time predictions with per-prediction confidence scores.
Collaborative Filtering · Content-Based · MyAnimeList · 2025
Designed a hybrid recommender over 17,000+ MyAnimeList titles using KNN-based collaborative filtering combined with cosine similarity content-based filtering. Features include:
- Genre-first onboarding to solve the cold-start problem
- A dislike feedback loop that progressively filters similar candidates from future results
- Google AI Essentials — 2025
- English for IT — Cisco Networking Academy, 2025
- Python for Everybody — University of Michigan, 2023
- Data Science fundamentals & Python depth
- Consistency and deliberate practice
Available for full-time roles from June 2026 · Open to relocation