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SHWETA0920/README.md
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Shweta Gupta

Full Stack Developer · AI/ML & RAG Systems


👋 About Me

I'm a fourth-year Computer Science student at KIIT University, building full-stack applications and AI/ML systems — from RAG pipelines to production-style data platforms. I care about shipping things that actually work end-to-end, not just prototypes.

Currently prepping for placements and going deeper into data engineering, backend architecture, and applied ML.


🌐 Connect


🛠️ Tech Stack

Languages
C++ Python JavaScript

Frontend
React Vite Tailwind

Backend
Node.js Express Flask

Data
PostgreSQL Prisma Redis

ML
Scikit-learn TensorFlow

AI / RAG
FAISS · pgvector · HuggingFace Transformers · Groq (Llama 3.3 70B) · Tree-sitter

💼 Featured Projects


🧠 CodeAtlas — RAG-Based Codebase Intelligence

A retrieval-augmented system that lets you query a codebase in natural language and get accurate, context-aware answers.

Metric Result
Precision@10 100%
Avg. query latency ~8.75s
Indexed 106 chunks · 33 files · 20+ languages

Next.js Flask FAISS pgvector HuggingFace Groq Tree-sitter


🔁 DSA Recall — Spaced-Repetition DSA Platform

A full-stack platform for retaining data structures & algorithms knowledge using spaced repetition tuned for coding practice.

Metric Result
Algorithm SM-2, adapted with DSA-specific weighting
Coverage 18 DSA topics · 7 mistake types tracked
Extras Judge0 execution · Redis caching · Chrome extension

React Vite Node.js Express PostgreSQL (Neon) Prisma Redis Judge0 Groq


🌾 KrishiCare — AI-Driven Agri-Tech Platform

An agriculture platform combining crop recommendation, rainfall forecasting, and plant disease detection in one product.

Metric Result
Crop recommendation (Random Forest) 99.3% accuracy, 22 classes
Rainfall forecasting (Stacked Ensemble) R² = 0.81, MAE = 35.96mm
Disease detection CNN, deployed Flask backend

React Flask Scikit-learn Random Forest CNN


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