Urban Air Quality Prediction Using Temporal ML Models
How I built a machine learning pipeline to predict VOCs, O₃, and NOx concentrations in urban environments — from raw sensor data to real-time forecasts using PyTorch TFT.
Architecting Scalable Full Stack Systems From Scratch
A deep dive into design decisions behind building scalable full-stack applications — from database schema to REST API contracts and frontend state management.
CI/CD, Docker, and Zero-Downtime Deployments
Practical lessons from setting up automated deployment pipelines — containerizing apps with Docker, writing CI/CD workflows, and shipping without breaking production.
DSA Patterns That Actually Matter in Interviews
A pragmatic guide to the 12 DSA patterns — sliding window, two pointers, monotonic stacks — with real implementations and when to apply each one.
Designing AI Systems That Scale Beyond the Prototype
The gap between a working ML model and a production AI system is enormous. Inference pipelines, latency, model versioning, and serving at scale.
Flutter Architecture Patterns for Production Apps
What I learned shipping Flutter apps to production — clean architecture, state management with Riverpod, and how to structure code that survives a growing team.