GitHub Codespaces
replit
StackBlitz
CloudShell
vscode.dev
CodeTasty
AWS Cloud9
StackHive
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Apache Zeppelin
Azure Synapse Analytics
Deepnote
Google BigQuery
GeoSpock
Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.
Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.
GitHub Codespacesfast, easy to create container, clear bill
I have used many alternative platform but nothing comes close to this
Smooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.
Based on our record, GitHub Codespaces seems to be a lot more popular than Saturn Cloud. While we know about 152 links to GitHub Codespaces, we've tracked only 7 mentions of Saturn Cloud. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
First, remote dev environments became table stakes. GitHub Codespaces, Gitpod, and self-hosted dev containers became how serious teams worked. Every engineer I know who ships to production now SSHs into a box they didn't provision, edits files with whatever editor is installed, and commits from a terminal. An IDE-bound agent requires you to also forward your IDE to the remote box, which most people don't bother... - Source: dev.to / 3 months ago
This package provides support for managing GitHub Codespaces in Emacs and connecting to them via TRAMP. It provides a handy completing-read UI that lets you choose from all your created codespaces. - Source: dev.to / 5 months ago
GitHub Codespaces provides 60 hours of free compute time every month, which is more than enough for scoped home assignments or interviews. Itโs a full VSCode in the browser at github.dev or vscode.dev. - Source: dev.to / 8 months ago
GitHub Codespaces - Cloud development. - Source: dev.to / about 1 year ago
https://github.com/features/codespaces All you need is a well-defined .devcontainer file. Debugging, extensions, collaborative coding, dependant services, OS libraries, as much RAM as you need (as opposed to what you have), specific NodeJS Versions โ all with a single click. - Source: Hacker News / over 1 year ago
After the MLOps tooling evaluation, our focus shifted to data engineering. Some teams in the company were already using tools like Dask and xarray to manage and process their datasets. The architect was determined to build a data lake for the organization. The vision was to make xarray datasets accessible via Intake, using a Dask-capable computing platform. For the compute platform, we explored services like... - Source: dev.to / over 1 year ago
Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: over 3 years ago
SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 3 years ago
I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ). There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 3 years ago
* How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / over 4 years ago
replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages โ without spending a second on setup.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
StackBlitz - Online VS Code Editor for Angular and React
Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics
CloudShell - Cloud Shell is a free admin machine with browser-based command-line access for managing your infrastructure and applications on Google Cloud Platform.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.