# 머신러닝시스템 2024
[![halla-img]][halla-url]
[![course-img]][course-url]
[![lecture-img]][lecture-url]
[![pypi-image]][pypi-url]
[![version-image]][release-url]
[![release-date-image]][release-url]
[![license-image]][license-url]
[![codecov][codecov-image]][codecov-url]
[![jupyter-book-image]][docs-url]
<!-- Links: -->
[halla-img]: https://img.shields.io/badge/CHU-halla.ai-blue
[halla-url]: https://halla.ai
[course-img]: https://img.shields.io/badge/course-entelecheia.ai-blue
[course-url]: https://course.entelecheia.ai
[lecture-img]: https://img.shields.io/badge/lecture-entelecheia.ai-blue
[lecture-url]: https://lecture.entelecheia.ai
[codecov-image]: https://codecov.io/gh/chu-aie/mlops-2024/branch/main/graph/badge.svg?token=6OxfwdlW4Y
[codecov-url]: https://codecov.io/gh/chu-aie/mlops-2024
[pypi-image]: https://img.shields.io/pypi/v/mlops2024
[license-image]: https://img.shields.io/github/license/chu-aie/mlops-2024
[license-url]: https://github.com/chu-aie/mlops-2024/blob/main/LICENSE
[version-image]: https://img.shields.io/github/v/release/chu-aie/mlops-2024?sort=semver
[release-date-image]: https://img.shields.io/github/release-date/chu-aie/mlops-2024
[release-url]: https://github.com/chu-aie/mlops-2024/releases
[jupyter-book-image]: https://jupyterbook.org/en/stable/_images/badge.svg
[repo-url]: https://github.com/chu-aie/mlops-2024
[pypi-url]: https://pypi.org/project/mlops2024
[docs-url]: https://mlops2024.halla.ai
[changelog]: https://github.com/chu-aie/mlops-2024/blob/main/CHANGELOG.md
[contributing guidelines]: https://github.com/chu-aie/mlops-2024/blob/main/CONTRIBUTING.md
<!-- Links: -->
Machine Learning Systems Design
- Documentation: [https://mlops2024.halla.ai][docs-url]
- GitHub: [https://github.com/chu-aie/mlops-2024][repo-url]
- PyPI: [https://pypi.org/project/mlops2024][pypi-url]
이 수업은 실제 운영 환경에서 기계 학습 시스템의 설계, 구현 및 관리에 대한 실질적인 측면을 다룹니다. 본 과정은 학생들에게 기계 학습 워크플로를 기존 소프트웨어 개발 및 운영 프로세스와 원활하게 통합하는 데 필요한 기술을 제공합니다. 이 과정에서는 DevOps, MLOps 및 보안 관행을 강조합니다. 학생들은 실습 프로젝트를 통해 dot 파일, git, Docker, Kubernetes, CI/CD 파이프라인, Weights & Biases 등 첨단 도구와 방법론을 사용하여 강력한 기계 학습 모델을 구축, 배포하고 유지 관리합니다. 또한, 이 과정은 학생들에게 GitOps, DevSecOps 및 LLMOps의 새로운 분야를 소개하여 실제 기계 학습 애플리케이션의 복잡성에 대비합니다.
## Installation
To install the MLOps 2024 package, use the following command:
```
pip install mlops2024
```
Or
```
pip install --user mlops2024
```
The `--user` flag is optional and can be used to install the package in the user's home directory instead of the system-wide location.
## Usage
To use the MLOps 2024 CLI, run the following command:
```
mlops2024 [OPTIONS]
```
If no option is provided, the website of the book will open in the default web browser.
### Options
The following options are available:
- `--version`: Show the version of the package and exit.
- `-b`, `--build`: Build the book.
- `-l`, `--local`: Open the locally built HTML version of the book in the browser.
- `--help`: Show the help message and exit.
### Examples
1. To build the book, use the following command:
```
mlops2024 --build
```
This will trigger the build process for the book.
2. To open the locally built HTML version of the book in the browser, use the following command:
```
mlops2024 --local
```
This will open the book's HTML file in your default web browser.
3. To view the version of the package, use the following command:
```
mlops2024 --version
```
This will display the version number of the MLOps 2024 package.
For more information and additional options, run `mlops2024 --help` to see the help message.
## Changelog
See the [CHANGELOG] for more information.
## Contributing
Contributions are welcome! Please see the [contributing guidelines] for more information.
## License
This project is released under the [CC-BY-4.0 License][license-url].
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"description": "# \uba38\uc2e0\ub7ec\ub2dd\uc2dc\uc2a4\ud15c 2024\n\n[![halla-img]][halla-url]\n[![course-img]][course-url]\n[![lecture-img]][lecture-url]\n[![pypi-image]][pypi-url]\n[![version-image]][release-url]\n[![release-date-image]][release-url]\n[![license-image]][license-url]\n[![codecov][codecov-image]][codecov-url]\n[![jupyter-book-image]][docs-url]\n\n<!-- Links: -->\n\n[halla-img]: https://img.shields.io/badge/CHU-halla.ai-blue\n[halla-url]: https://halla.ai\n[course-img]: https://img.shields.io/badge/course-entelecheia.ai-blue\n[course-url]: https://course.entelecheia.ai\n[lecture-img]: https://img.shields.io/badge/lecture-entelecheia.ai-blue\n[lecture-url]: https://lecture.entelecheia.ai\n[codecov-image]: https://codecov.io/gh/chu-aie/mlops-2024/branch/main/graph/badge.svg?token=6OxfwdlW4Y\n[codecov-url]: https://codecov.io/gh/chu-aie/mlops-2024\n[pypi-image]: https://img.shields.io/pypi/v/mlops2024\n[license-image]: https://img.shields.io/github/license/chu-aie/mlops-2024\n[license-url]: https://github.com/chu-aie/mlops-2024/blob/main/LICENSE\n[version-image]: https://img.shields.io/github/v/release/chu-aie/mlops-2024?sort=semver\n[release-date-image]: https://img.shields.io/github/release-date/chu-aie/mlops-2024\n[release-url]: https://github.com/chu-aie/mlops-2024/releases\n[jupyter-book-image]: https://jupyterbook.org/en/stable/_images/badge.svg\n[repo-url]: https://github.com/chu-aie/mlops-2024\n[pypi-url]: https://pypi.org/project/mlops2024\n[docs-url]: https://mlops2024.halla.ai\n[changelog]: https://github.com/chu-aie/mlops-2024/blob/main/CHANGELOG.md\n[contributing guidelines]: https://github.com/chu-aie/mlops-2024/blob/main/CONTRIBUTING.md\n\n<!-- Links: -->\n\nMachine Learning Systems Design\n\n- Documentation: [https://mlops2024.halla.ai][docs-url]\n- GitHub: [https://github.com/chu-aie/mlops-2024][repo-url]\n- PyPI: [https://pypi.org/project/mlops2024][pypi-url]\n\n\uc774 \uc218\uc5c5\uc740 \uc2e4\uc81c \uc6b4\uc601 \ud658\uacbd\uc5d0\uc11c \uae30\uacc4 \ud559\uc2b5 \uc2dc\uc2a4\ud15c\uc758 \uc124\uacc4, \uad6c\ud604 \ubc0f \uad00\ub9ac\uc5d0 \ub300\ud55c \uc2e4\uc9c8\uc801\uc778 \uce21\uba74\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \ubcf8 \uacfc\uc815\uc740 \ud559\uc0dd\ub4e4\uc5d0\uac8c \uae30\uacc4 \ud559\uc2b5 \uc6cc\ud06c\ud50c\ub85c\ub97c \uae30\uc874 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uac1c\ubc1c \ubc0f \uc6b4\uc601 \ud504\ub85c\uc138\uc2a4\uc640 \uc6d0\ud65c\ud558\uac8c \ud1b5\ud569\ud558\ub294 \ub370 \ud544\uc694\ud55c \uae30\uc220\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc5d0\uc11c\ub294 DevOps, MLOps \ubc0f \ubcf4\uc548 \uad00\ud589\uc744 \uac15\uc870\ud569\ub2c8\ub2e4. \ud559\uc0dd\ub4e4\uc740 \uc2e4\uc2b5 \ud504\ub85c\uc81d\ud2b8\ub97c \ud1b5\ud574 dot \ud30c\uc77c, git, Docker, Kubernetes, CI/CD \ud30c\uc774\ud504\ub77c\uc778, Weights & Biases \ub4f1 \ucca8\ub2e8 \ub3c4\uad6c\uc640 \ubc29\ubc95\ub860\uc744 \uc0ac\uc6a9\ud558\uc5ec \uac15\ub825\ud55c \uae30\uacc4 \ud559\uc2b5 \ubaa8\ub378\uc744 \uad6c\ucd95, \ubc30\ud3ec\ud558\uace0 \uc720\uc9c0 \uad00\ub9ac\ud569\ub2c8\ub2e4. \ub610\ud55c, \uc774 \uacfc\uc815\uc740 \ud559\uc0dd\ub4e4\uc5d0\uac8c GitOps, DevSecOps \ubc0f LLMOps\uc758 \uc0c8\ub85c\uc6b4 \ubd84\uc57c\ub97c \uc18c\uac1c\ud558\uc5ec \uc2e4\uc81c \uae30\uacc4 \ud559\uc2b5 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc758 \ubcf5\uc7a1\uc131\uc5d0 \ub300\ube44\ud569\ub2c8\ub2e4.\n\n## Installation\n\nTo install the MLOps 2024 package, use the following command:\n\n```\npip install mlops2024\n```\n\nOr\n\n```\npip install --user mlops2024\n```\n\nThe `--user` flag is optional and can be used to install the package in the user's home directory instead of the system-wide location.\n\n## Usage\n\nTo use the MLOps 2024 CLI, run the following command:\n\n```\nmlops2024 [OPTIONS]\n```\n\nIf no option is provided, the website of the book will open in the default web browser.\n\n### Options\n\nThe following options are available:\n\n- `--version`: Show the version of the package and exit.\n- `-b`, `--build`: Build the book.\n- `-l`, `--local`: Open the locally built HTML version of the book in the browser.\n- `--help`: Show the help message and exit.\n\n### Examples\n\n1. 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