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MLOps Pipeline Templates

$49

End-to-end ML pipeline templates with feature engineering, training, evaluation, and deployment stages.

📁 4 files🏷 v1.0.0
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📁 File Structure 4 files

mlops-pipeline-templates/ ├── LICENSE ├── README.md └── configs/ ├── development.yaml └── production.yaml

📖 Documentation Preview README excerpt

MLOps Pipeline Templates

End-to-end ML pipeline templates with feature engineering, training, evaluation, and deployment stages.

Contents

  • configs/development.yaml
  • configs/production.yaml

Quick Start

1. Extract the ZIP archive

2. Review the README and documentation

3. Customize configuration files for your environment

4. Follow the setup guide for your specific use case

Requirements

  • Python 3.10+ (for Python scripts)
  • Relevant CLI tools for your platform
  • Access to your target environment

License

MIT License — see LICENSE file.

Support

Questions or issues? Email megafolder122122@hotmail.com

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Part of [Ml Engineer](https://inity13.github.io/ml-engineer-toolkit/)

📄 Code Sample .yaml preview

configs/development.yaml # MLOps Pipeline Templates — Development Configuration environment: development log_level: DEBUG server: host: "127.0.0.1" port: 8080 workers: 1 timeout: 60 database: host: "localhost" port: 5432 name: "dev_db" pool_size: 5 cache: backend: redis url: "redis://localhost:6379" ttl: 60
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