---
title: "Discussion on \"Building a Full-Stack AI-Powered Municipal Civic Issue Management System from Scratch\" | Hashnode"
description: "Discussion on \"Building a Full-Stack AI-Powered Municipal Civic Issue Management System from Scratch\". From 200 rows to a deployed ML system — NLP, TF-IDF, Logistic Regression, XGBoost, FastAPI, React, and full cloud deployment explained step by step."
url: "https://hashnode.com/posts/building-a-full-stack-ai-powered-municipal-civic-issue-management-system-from-scratch/69ea8d54904b915438bf4a18"
---

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# [Building a Full-Stack AI-Powered Municipal Civic Issue Management System from Scratch](https://ai-ml-datascience-from-scratch.hashnode.dev/building-a-full-stack-ai-powered-municipal-civic-issue-management-system-from-scratch?utm_source=hashnode&utm_medium=feed)

From 200 rows to a deployed ML system — NLP, TF-IDF, Logistic Regression, XGBoost, FastAPI, React, and full cloud deployment explained step by step.

Apr 23 · 14 min read · ai-ml-datascience-from-scratch.hashnode.dev  
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-   [#tf-idf](https://hashnode.com/tag/tf-idf)

## Written by

[wajahat taj](https://hashnode.com/@Wajahattaj)

@Wajahattaj · islamabad

  
[View profile](https://hashnode.com/@Wajahattaj)

Software Engineering student at FAST-NUCES University.

Software Engineering student at FAST-NUCES building full-stack AI-powered systems end-to-end. I work across the full stack: Frontend: React.js & Next.js Backend: FastAPI & Express.js Mobile: React Native ML & NLP: scikit-learn, TF-IDF, Logistic Regression, Random Forest , XG-Boost , ANN. Deployment: Docker, Render, Vercel I don't just study ML concepts — I integrate them into real products and ship them. Currently going deeper into backend architecture, scalable API design, MLOps, and production deployment pipelines. Because writing code is just the beginning — shipping systems that work in the real world is the goal.

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