The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science with Python. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated.
What's the difference between this Python project and similar ones?
Combines various common (open-source) development tools (Jupyter, JupyterLab, VS Code, ...) into one integrated Docker container.
Completely web-based with a high extensibility and lots of features.
--
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/1344
**Author:** [@lukasmasuch](https://github.com/lukasmasuch)
**Created:** 9/5/2019
**Status:** ❌ Closed
**Base:** `master` ← **Head:** `patch-1`
---
### 📝 Commits (1)
- [`c210634`](https://github.com/vinta/awesome-python/commit/c21063498c3dd110687aebe14618c7583c7f78c2) Add ML Workspace
### 📊 Changes
**1 file changed** (+2 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+2 -0)
</details>
### 📄 Description
## What is this Python project?
The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science with Python. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated.
## What's the difference between this Python project and similar ones?
- Combines various common (open-source) development tools (Jupyter, JupyterLab, VS Code, ...) into one integrated Docker container.
- Completely web-based with a high extensibility and lots of features.
--
Anyone who agrees with this pull request could vote for it by adding a :+1: to it, and usually, the maintainer will merge it when votes reach **20**.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.
📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/1344
Author: @lukasmasuch
Created: 9/5/2019
Status: ❌ Closed
Base:
master← Head:patch-1📝 Commits (1)
c210634Add ML Workspace📊 Changes
1 file changed (+2 additions, -0 deletions)
View changed files
📝
README.md(+2 -0)📄 Description
What is this Python project?
The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science with Python. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated.
What's the difference between this Python project and similar ones?
--
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.