I build end-to-end systems where data actually goes somewhere — not just notebooks that rot.

I’m a B.Tech student focused on Machine Learning, backend engineering, and real-world deployments.

I enjoy working on projects where:

• data flows through multiple stages (ingestion → processing → modeling → presentation)
• ML models are part of a larger system
• deployment is treated as a first-class problem, not an afterthought

I care about how things work end-to-end, not just whether the model trains.

• Practical ML pipelines and feature engineering
• Model evaluation and iteration
• ML systems that integrate with real applications

• CNNs for image-based tasks
• LSTM-based sequence & NLP models
• PyTorch & TensorFlow (hands-on, not theoretical)

• Designing APIs around ML workflows
• Model inference services using FastAPI / Flask

• ETL pipelines
• Data cleaning, transformation, and aggregation

• Dockerized applications
• AWS EC2 deployments
• Basic CI/CD with GitHub Actions

• Next.js frontends for data visualization and insights

ETL Pipeline + Frontend Dashboard

• Built a complete ETL pipeline to process raw football data
• Cleaned, transformed, and structured league, team, and match data
• Served processed insights to a frontend dashboard
• Deployed frontend for public access

Focus: data pipelines, system design, and turning raw data into usable insights.

ML Pipeline + Backend + Deployment

• CNN-based deep learning models for medical images
• End-to-end ML pipeline (training → inference)
• FastAPI backend exposing prediction APIs
• Dockerized and deployed on AWS EC2

Focus: ML-to-production workflows and backend integration.

• Audio preprocessing with MFCC feature extraction
• Neural network–based classification
• Trained and evaluated on a ~100-song dataset
• Experiments conducted using Google Colab

Focus: audio ML, feature engineering, and non-visual ML domains.

• Fully custom portfolio built with Next.js
• Responsive, clean, and performance-focused
• Structured presentation of projects and skills
• Publicly deployed

Focus: presenting technical work professionally.

Python • JavaScript • C • C++

PyTorch • TensorFlow / Keras • NumPy • Pandas • Scikit-Learn

FastAPI • Flask • Node.js (basic)

MongoDB (beginner) • MySQL • Firebase

Docker • Git & GitHub • AWS EC2 • GitHub Actions

Next.js • React • Tailwind CSS

Google Colab • VS Code • Jupyter Notebooks

I’m always interested in discussions around:

• machine learning systems
• backend engineering
• data pipelines
• deploying things that break before they work

If that’s your space too, feel free to explore my repositories or connect with me here on GitHub.