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mlops

Hybrid cloud-edge ML system for predictive rain control with automated retraining, monitoring, and Raspberry Pi hardware actuation.

High-performance interactive companion dashboard for AI recommendation systems. Built by Pavan Badempet.

Official GitLab profile and developer identity of Pavan Badempet — Data Platform Engineer & MLOps Architect.

Enterprise Clinical AI & Healthcare Lakehouse Platform: FHIR R4 / OMOP CDM compliance, PySpark Tabular Foundation Models, and HIPAA/ABDM-ready chatbot. Engineered by Pavan Badempet.

Personal Developer Portfolio & Engineering Showcase of Pavan Badempet | Data Platform, MLOps, Lakehouses, and Big Data Architecture.

Public pages of the ANR project "FATES-MLOps"

A generic implementation roadmap that can facilitate MLOps for any ML problem in detail. This roadmap is intended for reducing problem solutioning, and using problem solving instead.

VERA (Video Extraction and Recognition Analysis) is a fully on-premises video OCR pipeline for extracting and recognizing text (license plates, street signs, billboards) from dashcam/driving footage. Built with PaddleOCR 3.x, OpenCV, FastAPI, PostgreSQL, and MinIO, with a PySide6 desktop GUI. Consists of two components: vera-engine (OCR pipeline, backend API, CLI) and vera-desktop (GUI layer). No cloud inference, all processing runs locally.

Check game monitor and download game here: https://omni-synesis.onrender.com/

BAVAR-BLED là một kiến trúc lai kết hợp Bayesian Model Averaging, Vector Autoregression, Black-Litterman dưới phân phối Elip, Transformer, CNN và TD3 để xây dựng chiến lược phân bổ danh mục động, có khả năng thích ứng theo trạng thái thị trường và kiểm soát rủi ro đuôi dày.

Bootstrap a self-service AI platform with GitOps

CICD project for a sentiment analyzer (deployment on lightining.ai gpu)

Enterprise-grade Medical AI Platform with FastAPI, Kubernetes, Monitoring and AKS-ready deployment architecture.

Production-ready RAG starter: hybrid search, chunking strategies, observability (Prometheus/Grafana), MLflow tracking, drift detection, GDPR deletion, and evaluation. The parts the tutorials skip.

Automated LLM Benchmarking on GPU - tokens/sec, latency percentiles, VRAM profiling, multi-format support (HuggingFace, GGUF, GPTQ)

https://ayinedjimi-consultants.fr

Automated Dataset Creation & Publishing Pipeline - Scrape, clean, transform, validate and publish datasets to HuggingFace Hub

https://ayinedjimi-consultants.fr

Hybrid credit intelligence platform using XGBoost, RAG, Terraform and GitLab CI/CD.