ML-Workspace
openvscode-server
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ML-Workspace | openvscode-server | |
---|---|---|
7 | 125 | |
3,317 | 4,687 | |
0.8% | 2.2% | |
2.7 | 0.0 | |
5 months ago | 7 days ago | |
Jupyter Notebook | TypeScript | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ML-Workspace
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
- ML-Workspace
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Coding for machine learning on Tab S8?
The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)
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Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- All-in-One Docker Based IDE for Data Science and ML
- Visual Studio Code now available as Web based editor for GitHub repos
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[P] Install or update CUDA, NVIDIA Drivers, Pytorch, Tensorflow, and CuDNN with a single command: Lambda Stack
I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.
openvscode-server
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Reviving decade-old Macs with antiX and MX Linux (2022)
> Yeah, sadly there are entry level laptops cheaper than a phone or said monitor plus a keyboard and mouse
Many people already have a monitor, mouse, and keyboard lying around. They'll also have a phone already. Plus, there are very cheap docks where you can just slide your phone into a laptop shell, priced similarly to the worst and most awful Chromebooks imaginable.
> So nothing works offline.
You can run a vscode server on your phone (https://github.com/gitpod-io/openvscode-server/releases). What's lacking is the VSCode GUI, so pointing a browser at http://[::1]:8080/ will work just fine.
- [Self Hosted] Alternative auto-hébergée aux codepaces
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Building a remote/cloud dev box IDE specifically for digital nomads. What do you want?
This already exists!! https://www.gitpod.io/
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Understanding the Networking Basics of Lambda to RDS Connectivity
The next part is the 'Public access' parameter which needs to be aligned with the DB Subnet Group configuration. When set to No, the provisioned ENI will only have Private IP. If you try to access it from the Internet, your PC or a cloud development environment such as Gitpod that would obviously not be accessible. However, if you set it to Yes, the ENI will also have a Public IP and a Public hostname (DNS endpoint). This settings can be changed without the need to re-provision the RDS which is quite handy.
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Crazy coworker manages entire development environment in single docker container
https://www.gitpod.io/ does this
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Self-hosted alternative to Codespaces? (With .devcontainer support)
Not sure what .devcontainer means, but you can take a look to https://github.com/gitpod-io/openvscode-server or https://github.com/coder/code-server
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Does anyone have a solution to replace my laptop?
I am using this project (https://github.com/gitpod-io/openvscode-server/) to run on my Linux box, then I can access it's server through my web browser.
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️Appwrite + Gitpod: One Click Setup
We look forward to integrating more with Gitpod in the future! Check out the Gitpod homepage for more information and new development environment templates.
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
I suggest you check out https://www.gitpod.io, which does more general provisioning of GitOps clusters/Pods in their managed Kubernetes clusters. It's not specifically ML, but we've looked at it for POC ML projects that want basic hosting.
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A second look at Amazon CodeCatalyst – CI/CD natively on AWS to empower developers to deliver faster and reduce heavy lifting
The last option - the Dev Environments - is the most exciting functionality - it gives you the possibility to host development environments (similar to Gitpod) on AWS using Cloud9 but also, and this is really cool, using Visual Studio or JetBrains IDEs. When using that option, the IDE on your local PC is only the "presentation layer", the source code is stored and run on an AWS instance and the IDE uses remote connectivity to talk to the Dev Environment in the background.
What are some alternatives?
JupyterLab - JupyterLab computational environment.
Code-Server - VS Code in the browser
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
vscode-dev-containers - NOTE: Most of the contents of this repository have been migrated to the new devcontainers GitHub org (https://github.com/devcontainers). See https://github.com/devcontainers/template-starter and https://github.com/devcontainers/feature-starter for information on creating your own!
keytotext - Keywords to Sentences
openvsx - An open-source registry for VS Code extensions
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
template-docker-compose - A Docker Compose template, configured for Gitpod (www.gitpod.io) to give you pre-built, ephemeral development environments in the cloud.
gitpod - The developer platform for on-demand cloud development environments to create software faster and more securely.
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)
vscodium - binary releases of VS Code without MS branding/telemetry/licensing