Freelancers using XGBoost in JaipurFreelancers using XGBoost in Jaipur
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Disha Chopra's avatar
Disha Chopra
Jaipur, India
Full-Stack Developer building AI Agents & RAG Systems
New to Contra
Full-Stack Developer building AI Agents & RAG Systems
Cover image for FinSense - AI-Powered NPA Prevention
FinSense - AI-Powered NPA Prevention Platform for Banking AI-powered, post-disbursement loan health monitoring system built for SBI-scale banking use cases. Continuously monitors borrower financial behavior after loan disbursement, scores risk on a 0–100 scale across 4 tiers using XGBoost with SHAP-based explainability, and deploys a conversational AI agent to proactively engage at-risk borrowers 60–90 days before default — instead of only scoring creditworthiness at application time like traditional systems. Built the FastAPI backend (loan, risk, agent, and dashboard routers), automated risk re-scoring via Celery + Redis, and real-time dashboard updates via WebSockets, with a React + Tailwind frontend for officer-facing risk visualization.
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Cover image for Financial Decision Intelligence Platform —
Financial Decision Intelligence Platform — Multi-Agent Risk Analysis Multi-agent platform (LangGraph) that ingests SEC 10-K filings via XBRL extraction, runs Altman Z-Score and Piotroski F-Score risk models, and generates investment committee reports. Pipeline includes RAG-based risk retrieval (FAISS + Sentence Transformers), XGBoost ML inference, and Gemini API report generation — served through a FastAPI backend with /analyze, /compare, and /report endpoints for multi-company investment ranking. Stack: Python, LangChain, LangGraph, FAISS, XGBoost, FastAPI
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Cover image for RepoSphere - GitHub-Inspired Version Control
RepoSphere - GitHub-Inspired Version Control Platform Full-stack, GitHub-inspired platform with JWT authentication, repository management, issue tracking, and real-time search. Built a RESTful API with user dashboards, and reduced code redundancy by 35% through modular architecture. Deployed on AWS Amplify.
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Cover image for SENTINEL - Edge AI Driver
SENTINEL - Edge AI Driver Assistance System Backend Lead for an edge AI ADAS (driver assistance) system built for Indian road conditions. Multi-stage ML pipeline covering sensor fusion, scene classification, risk scoring, GradCAM/XAI explainability, and federated learning. Built the backend and deployment pipeline, integrating ONNX and PyTorch runtimes to serve model inference in production.
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XGBoost(2)