Writing & Notes
Thoughts on data science, ML engineering, and building real projects — written from what I've actually shipped.
11 Sept 2026
LMS Backend: The Unglamorous Infrastructure Behind a Learning Platform
Node.js, Express, MongoDB, and Cloudinary powering a Learning Management System backend — and why documenting the API with Swagger from day one saved real time.
11 Sept 2026
Building a Resume Parser Backend: Turning Unstructured PDFs Into Structured Data
An API-first backend service for parsing resumes — and why extracting structured fields from a PDF is a genuinely underrated, messy data engineering problem.
11 Sept 2026
Applying LLM APIs to a Real Conversational Task, Not Just a Prompt Playground
A focused Generative AI project built around applying large language model APIs to an actual practical task, rather than just demonstrating that an API call works.
11 Sept 2026
DVC for Data Versioning: Treating Datasets Like Code
Git tracks your code changes. DVC tracks your data and model changes the same way — here's why that distinction matters once an ML project has more than one contributor or one training run.
11 Sept 2026
Turning IPL Data Into an Actual Dashboard, Not Just a Chart Dump
A TypeScript + Python data analytics project that takes raw IPL match data and turns it into structured, decision-ready insight — the kind of pipeline real analytics work looks like.
11 Sept 2026
What an End-to-End MLOps Pipeline Actually Needs (Beyond Just Training a Model)
Training a model is the easy part. This project is about the parts around it — preprocessing, evaluation, tracking, and CI/CD — that make a model deployable, not just accurate.
11 Sept 2026
Python Data Science Mastery: My Running Log of Learning NumPy, Pandas, and Matplotlib Properly
A structured, growing collection of Python data science fundamentals — not a random notes dump, but a curriculum I built for myself and now teach from.
11 Sept 2026
Predicting Test Scores from Study Hours: A Simple Linear Regression Project, Done Properly
Not every ML project needs to be complex to be worth building well — a FastAPI + scikit-learn + Next.js app that predicts scores from study hours, with a real UI instead of a notebook.
11 Sept 2026
Quiz Application: Handling AI-Generated and Manually-Written Questions in One System
A quiz platform built with Next.js and NestJS where questions can come from a teacher or from an LLM — and both need to fit the same data model.
11 Sept 2026
Building a Production-Ready RAG Chatbot with Next.js, LangChain, and Pinecone
How retrieval-augmented generation actually works in practice — chunking, embeddings, vector search, and streaming — built as a chatbot that answers questions about my own portfolio.
11 Sept 2026
OmniConnect API: One Node.js Backend, Three Very Different Jobs
Employee management, student enrollment, media uploads, and real-time chat — all inside one modular Node.js API. Here's how keeping it modular kept it maintainable.
11 Sept 2026
HMS: Designing a Hospital Management System Around Roles, Not Just Features
Building a full-stack HMS with RBAC, AI diagnostics, and a live bed matrix — and why starting from "who uses this" instead of "what does this do" changes the whole architecture.
11 Sept 2026
Voxa: What It Takes to Build a Multimodal AI Tutor (Not Just Another Chatbot)
Chat, voice, and document intelligence in one tutoring platform — the design decisions behind combining three very different input modes into one coherent assistant.
11 Sept 2026
AutoScan AI: Reading License Plates in the Real World, Not Just Clean Test Images
Building a full ANPR pipeline with YOLOv8, EasyOCR, and Gemini — and why the hard part isn't detecting the plate, it's reading it correctly when the lighting is against you.
11 Sept 2026
Building a 3D DSA Visualizer That Actually Makes Algorithms Click
Why I built a real-time 3D engine for visualizing 110+ data structures and algorithms, and what it took to make sorting, trees, and graphs feel spatial instead of abstract.