mrx-link


Namemrx-link JSON
Version 1.2.0 PyPI version JSON
download
home_page
SummaryA simple AI/ML modeling tool, Linkā„¢ ensures a smoother flow and a better experience throughout the model development cycle.
upload_time2023-12-11 01:30:00
maintainer
docs_urlNone
author
requires_python>=3.8
licenseproprietary
keywords jupyter jupyterlab jupyterlab3
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            [![Binder](https://static.mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=Link_Intro.ipynb)

<div style="text-align:center"><p><img src="https://user-images.githubusercontent.com/18215796/186842421-4af16476-8c68-47e8-a941-c16d6bb1c43b.png" /></p></div>

# Link

> _A simple AI/ML modeling tool developed as an extension of JupyterLab, Link ensures a smoother flow and a better experience throughout the model development cycle._

[Discussions](https://makinarocks-link.readme.io/discuss) | [Docs](https://makinarocks-link.readme.io/docs) | [Link SDK](https://makinarocks-link.readme.io/reference/introduction) | [Release Note](https://makinarocks-link.readme.io/changelog) | [Website](https://link.makinarocks.ai) | [Youtube](https://youtu.be/uM2uPG-1eQQ) | [Technical Support](https://link.makinarocks.ai/technical_support.html)

## Usage Environment

| Supported Platform | Linux (AMD64, ARM64) / macOS (Intel, Apple Silicon) / Windows |
| ------------------ | ------------------------------------------------------------- |
| Python Version     | `3.8`, `3.9`, `3.10`                                          |
| Requirements       | Git                                                           |

## Getting Started

We recommend installing our program in a new virtual environment.

Step 1. Install Link with the following command.

```bash
python3 -m pip install --upgrade mrx-link
```

Step 2. After installation, run JupyterLab.

```bash
python3 -m jupyterlab
```

If you wish to install it as a Desktop Application, please download from [here](https://link.makinarocks.ai/download.html).<br/>
And if you want to try Link on your browser, please click [here](https://mybinder.org/v2/gh/makinarocks/makina-link-release/main?urlpath=lab/tree/Link-Intro.ipynb).

## Main Features

**_Pipeline Creation_**

Create a pipeline with notebook cells to improve code readability and reproducibility.

![pipeline_creation](https://user-images.githubusercontent.com/18215796/186842853-dbe3d0ec-7388-4706-9755-580e04dbf1db.gif)

**_Caching Management_**

Store execution results for respective cells to minimize redundant cell executions.

![caching_management](https://user-images.githubusercontent.com/18215796/186842403-66c6fabf-d395-4e76-8fdc-91145c869113.gif)

**_Remote Resources_**

Optimize the use of server resources by using separate resources for different pipeline components.

![remote_resources](https://user-images.githubusercontent.com/18215796/206979875-e486c0f3-a5f2-484a-90c3-72e321c91019.gif)

**_Hyper-Parameter Optimizer_**

Link provides a hyper-parameter feature, which works to find optimal hyper-parameters in an automated manner.

![hpo_multiple_edited](https://user-images.githubusercontent.com/18215796/206979329-38349f8c-b5f5-4892-be93-8839f277411e.gif)

**_Version Control_**

Link provides a version control feature, where you can easily view changes to your pipeline and merge conflicts.

![version_control](https://user-images.githubusercontent.com/18215796/186842427-6156ff9a-70ea-4345-8cb4-56aa95471aff.gif)

**_Link SDK_**

Link provides an SDK, where you can easily run the Link notebook file with the command line interface, and create, run, export pipelines with Python code. ([Learn more](https://makinarocks-link.readme.io/reference/introduction))

![link_sdk](https://user-images.githubusercontent.com/18215796/221751603-f08eee59-0c2b-4b76-a953-92d5283fc380.png)

**_Other Features_**

- Convert your pipelines to Kubeflow (`.yaml`) pipelines.
- Convert your components to executable Python (`.py`) code.

## Examples

- [Link Introduction](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=Link_Intro.ipynb)
- [Deep Q-Network Reinforcement Learning for the CartPole Environment](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Deep_Q-Network_Reinforcement_Learning.ipynb)
- [Denoising Autoencoder with PyTorch](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Denoising_Autoencoder.ipynb)
- [Iris Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Iris_EDA_and_Modeling.ipynb)
- [MNIST Image Classification with PyTorch](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/MNIST_Classification.ipynb)
- [MNIST Image Generation with VAE](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/MNIST_Generation_with_VAE.ipynb)
- [Sequential Data Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Text_Classification_with_RNN.ipynb)
- [Spiral-Distributed Data Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Spiral_Classification.ipynb)
- [Titanic Data EDA and Modeling](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Titanic_EDA_and_Modeling.ipynb)
- [XGBoost Example](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/XGBoost.ipynb)

## Help and Support

- Product Page: [https://link.makinarocks.ai](https://link.makinarocks.ai/index.html)
- Official Documentation: [https://makinarocks-link.readme.io/docs](https://makinarocks-link.readme.io/docs)
- Release Notes: [https://makinarocks-link.readme.io/changelog](https://makinarocks-link.readme.io/changelog)
- Technical Support: Contact [Technical Support](https://link.makinarocks.ai/technical_support.html) for any questions or issues

## Team

- Chan Baek ([@chan-python](https://github.com/chan-python))
- Daesung Kim ([@JakeisDaeSung](https://github.com/JakeisDaeSung))
- Dohu Jeon ([@adc0612](https://github.com/adc0612))
- Eunyoo Byeon ([@EunyooByeon](https://github.com/EunyooByeon))
- Hongji Kim ([@HongJi-Kim](https://github.com/HongJi-Kim))
- Hooncheol Shin ([@hunhoon21](https://github.com/hunhoon21))
- Hwiyeon Cho ([@hwyncho](https://github/com/hwyncho))
- Hyeonseok Shin ([@hyeonseok](https://github.com/hyeonseok))
- Jaeseong Choe ([@sorrychoe](https://github.com/sorrychoe))
- Jonghyeok Lee ([@daisy0y](https://github.com/daisy0y))
- Jungmin Park ([@jungminpark1234](https://github.com/jungminpark1234))
- Ryeong Yi ([@ryeongYi](https://github.com/ryeongYi))
- Sangwoo Shim ([@borishim](https://github.com/borishim))
- Woojin Cha ([@Xena123kiki](https://github.com/Xena123kiki))
- Yongjin Shin ([@YongjinShin306](https://github.com/YongjinShin306))

## Contributors

- Byoungwan Kim ([@bwkim71](https://github.com/bwkim71))
- Hwan Chang ([@aiworld-git](https://github.com/aiworld-git))

            

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    "description": "[![Binder](https://static.mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=Link_Intro.ipynb)\n\n<div style=\"text-align:center\"><p><img src=\"https://user-images.githubusercontent.com/18215796/186842421-4af16476-8c68-47e8-a941-c16d6bb1c43b.png\" /></p></div>\n\n# Link\n\n> _A simple AI/ML modeling tool developed as an extension of JupyterLab, Link ensures a smoother flow and a better experience throughout the model development cycle._\n\n[Discussions](https://makinarocks-link.readme.io/discuss) | [Docs](https://makinarocks-link.readme.io/docs) | [Link SDK](https://makinarocks-link.readme.io/reference/introduction) | [Release Note](https://makinarocks-link.readme.io/changelog) | [Website](https://link.makinarocks.ai) | [Youtube](https://youtu.be/uM2uPG-1eQQ) | [Technical Support](https://link.makinarocks.ai/technical_support.html)\n\n## Usage Environment\n\n| Supported Platform | Linux (AMD64, ARM64) / macOS (Intel, Apple Silicon) / Windows |\n| ------------------ | ------------------------------------------------------------- |\n| Python Version     | `3.8`, `3.9`, `3.10`                                          |\n| Requirements       | Git                                                           |\n\n## Getting Started\n\nWe recommend installing our program in a new virtual environment.\n\nStep 1. Install Link with the following command.\n\n```bash\npython3 -m pip install --upgrade mrx-link\n```\n\nStep 2. After installation, run JupyterLab.\n\n```bash\npython3 -m jupyterlab\n```\n\nIf you wish to install it as a Desktop Application, please download from [here](https://link.makinarocks.ai/download.html).<br/>\nAnd if you want to try Link on your browser, please click [here](https://mybinder.org/v2/gh/makinarocks/makina-link-release/main?urlpath=lab/tree/Link-Intro.ipynb).\n\n## Main Features\n\n**_Pipeline Creation_**\n\nCreate a pipeline with notebook cells to improve code readability and reproducibility.\n\n![pipeline_creation](https://user-images.githubusercontent.com/18215796/186842853-dbe3d0ec-7388-4706-9755-580e04dbf1db.gif)\n\n**_Caching Management_**\n\nStore execution results for respective cells to minimize redundant cell executions.\n\n![caching_management](https://user-images.githubusercontent.com/18215796/186842403-66c6fabf-d395-4e76-8fdc-91145c869113.gif)\n\n**_Remote Resources_**\n\nOptimize the use of server resources by using separate resources for different pipeline components.\n\n![remote_resources](https://user-images.githubusercontent.com/18215796/206979875-e486c0f3-a5f2-484a-90c3-72e321c91019.gif)\n\n**_Hyper-Parameter Optimizer_**\n\nLink provides a hyper-parameter feature, which works to find optimal hyper-parameters in an automated manner.\n\n![hpo_multiple_edited](https://user-images.githubusercontent.com/18215796/206979329-38349f8c-b5f5-4892-be93-8839f277411e.gif)\n\n**_Version Control_**\n\nLink provides a version control feature, where you can easily view changes to your pipeline and merge conflicts.\n\n![version_control](https://user-images.githubusercontent.com/18215796/186842427-6156ff9a-70ea-4345-8cb4-56aa95471aff.gif)\n\n**_Link SDK_**\n\nLink provides an SDK, where you can easily run the Link notebook file with the command line interface, and create, run, export pipelines with Python code. ([Learn more](https://makinarocks-link.readme.io/reference/introduction))\n\n![link_sdk](https://user-images.githubusercontent.com/18215796/221751603-f08eee59-0c2b-4b76-a953-92d5283fc380.png)\n\n**_Other Features_**\n\n- Convert your pipelines to Kubeflow (`.yaml`) pipelines.\n- Convert your components to executable Python (`.py`) code.\n\n## Examples\n\n- [Link Introduction](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=Link_Intro.ipynb)\n- [Deep Q-Network Reinforcement Learning for the CartPole Environment](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Deep_Q-Network_Reinforcement_Learning.ipynb)\n- [Denoising Autoencoder with PyTorch](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Denoising_Autoencoder.ipynb)\n- [Iris Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Iris_EDA_and_Modeling.ipynb)\n- [MNIST Image Classification with PyTorch](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/MNIST_Classification.ipynb)\n- [MNIST Image Generation with VAE](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/MNIST_Generation_with_VAE.ipynb)\n- [Sequential Data Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Text_Classification_with_RNN.ipynb)\n- [Spiral-Distributed Data Classification](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Spiral_Classification.ipynb)\n- [Titanic Data EDA and Modeling](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/Titanic_EDA_and_Modeling.ipynb)\n- [XGBoost Example](https://mybinder.org/v2/gh/makinarocks/mrx-link-binder/main?labpath=sample-notebooks/XGBoost.ipynb)\n\n## Help and Support\n\n- Product Page: [https://link.makinarocks.ai](https://link.makinarocks.ai/index.html)\n- Official Documentation: [https://makinarocks-link.readme.io/docs](https://makinarocks-link.readme.io/docs)\n- Release Notes: [https://makinarocks-link.readme.io/changelog](https://makinarocks-link.readme.io/changelog)\n- Technical Support: Contact [Technical Support](https://link.makinarocks.ai/technical_support.html) for any questions or issues\n\n## Team\n\n- Chan Baek ([@chan-python](https://github.com/chan-python))\n- Daesung Kim ([@JakeisDaeSung](https://github.com/JakeisDaeSung))\n- Dohu Jeon ([@adc0612](https://github.com/adc0612))\n- Eunyoo Byeon ([@EunyooByeon](https://github.com/EunyooByeon))\n- Hongji Kim ([@HongJi-Kim](https://github.com/HongJi-Kim))\n- Hooncheol Shin ([@hunhoon21](https://github.com/hunhoon21))\n- Hwiyeon Cho ([@hwyncho](https://github/com/hwyncho))\n- Hyeonseok Shin ([@hyeonseok](https://github.com/hyeonseok))\n- Jaeseong Choe ([@sorrychoe](https://github.com/sorrychoe))\n- Jonghyeok Lee ([@daisy0y](https://github.com/daisy0y))\n- Jungmin Park ([@jungminpark1234](https://github.com/jungminpark1234))\n- Ryeong Yi ([@ryeongYi](https://github.com/ryeongYi))\n- Sangwoo Shim ([@borishim](https://github.com/borishim))\n- Woojin Cha ([@Xena123kiki](https://github.com/Xena123kiki))\n- Yongjin Shin ([@YongjinShin306](https://github.com/YongjinShin306))\n\n## Contributors\n\n- Byoungwan Kim ([@bwkim71](https://github.com/bwkim71))\n- Hwan Chang ([@aiworld-git](https://github.com/aiworld-git))\n",
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