https://github.com/drsunday-ade/ai-systems-data-engineering

Data engineering + ML systems: lakehouse/ETL, streaming, feature store, MLOps, and model serving. Synthetic data → train → ONNX → FastAPI service + CI.
https://github.com/drsunday-ade/ai-systems-data-engineering

airflow data-en dbt dvc fastapi feature-store github-actions great-exp mlops onnx spark streaming

Last synced: 3 months ago
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Data engineering + ML systems: lakehouse/ETL, streaming, feature store, MLOps, and model serving. Synthetic data → train → ONNX → FastAPI service + CI.

• Host: GitHub
• URL: https://github.com/drsunday-ade/ai-systems-data-engineering
• Owner: drsunday-ade
• Created: 2025-09-01T23:16:33.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2025-09-01T23:17:38.000Z (10 months ago)
• Last Synced: 2025-09-02T01:11:35.059Z (10 months ago)
• Topics: airflow, data-en, dbt, dvc, fastapi, feature-store, github-actions, great-exp, mlops, onnx, spark, streaming
• Homepage:
• Size: 1.95 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# ai-systems-data-engineering

Data engineering + ML systems: lakehouse/ETL, streaming, feature store, MLOps, and model serving. Synthetic data → train → ONNX → FastAPI service + CI.

# AI Systems & Data Engineering

**Goal:** end-to-end, reproducible ML systems: ingest → validate → transform → feature store → train → export (ONNX) → serve (FastAPI) → CI.

## Quickstart

```bash

python -m venv .venv && source .venv/bin/activate

pip install -r requirements.txt

python etl/synth_data.py

python etl/transform.py

python etl/validate.py

python training/train.py

python training/export_onnx.py

uvicorn serving.app:app --reload