자동 평가 파이프라인 오케스트레이터
End-to-end Azure data engineering pipeline ingesting real-time earthquake data from the USGS API. Implements a Bronze–Silver–Gold lakehouse using Azure Data Factory, Databricks, ADLS Gen2, and Synapse Analytics, with both manual execution and fully automated daily-triggered workflows.
An engineering-grade, LLM-driven pipeline that transforms high-level Epics into complete test assets — Features, User Stories, Test Plans, Test Cases, and Playwright automation. Designed with step-wise generation, human-in-the-loop review, resumable execution, batching to avoid truncation, and versioned artifacts for traceability and evaluation.
AutomatonX is an advanced CI/CD pipeline automation framework designed to streamline software delivery and deployment processes
This project uses Mage to build a pipeline for ingesting, transforming NYC taxi data, and training a linear regression model. The model and artifact (dict vectorizer) are logged and registered with MLflow.
Workflow manager for building modular processing pipelines with structured configuration and flexible task orchestration
A comprehensive DevOps pipeline orchestration framework
This repo gives you insights on the data engineering project I built using public datasets from San Francisco open data portal.
This project implements a Retrieval-Augmented Generation (RAG) pipeline using Mage to manage large language models (LLMs) on an hourly schedule.
Add native flow-level dependency support to Prefect OSS with a lightweight @wait_for_deployments decorator
"End-to-end MLOps pipeline for image classification using ZenML, MLflow, and TensorFlow. Features automated training, continuous deployment, drift detection with Deepchecks, and a Streamlit frontend."
🌍 Ingest and transform real-time earthquake data using Azure tools to deliver reliable analytics-ready datasets for insightful decision-making.
🛠️ Streamline testing by automating asset generation from user stories to Playwright tests, ensuring a reviewable and efficient LLM-based pipeline.
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