Hashnode
DEV.to
Medium
GitHub
Stack Overflow
Ghost
Hacker Noon
Substack
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
HashnodeBased on our record, Hashnode should be more popular than Deepnote. It has been mentiond 136 times since March 2021. 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.
If you found this guide useful or have questions, donโt hesitate to drop a comment below. What was your first Docker project? Share your experiences, and letโs learn together! Donโt forget to follow me on Dev.to and Hashnode for more developer insights. Happy Dockering! - Source: dev.to / 3 months ago
So, let's say that you are writing a post on your website, but you also want to publish it on other platforms, like medium.com, dev.to or hashnode.com. There is no way you can compete with these domains in terms of domain authority. This means that, to Google, they are more valid sources of content then your small and less visited website. However, you can leverage the reach that those platforms can give you and... - Source: dev.to / 7 months ago
Hashnode Developer-focused blogging platform with built-in formatting, graphs, and custom domains. - Source: dev.to / about 1 year ago
We looked into a few different providers including GitBook, Docusaurus, Hashnode, Fern and Mintlify. There were various factors in the decision but the TLDR is that while we manage our SDKs with Fern, we chose Mintlify for docs as it had the best writing experience, supported custom React components, and was more affordable for hosting on a custom domain. Both Fern and Mintlify pull from the same single source of... - Source: dev.to / about 1 year ago
Hashnode write dev blogs and build a reputation. - Source: dev.to / about 1 year ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / about 2 years ago
- https://deepnote.com -- also extensive AI integration and realtime collaboration. - Source: Hacker News / about 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / over 2 years ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 3 years ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / about 3 years ago
DEV.to - Where software engineers connect, build their resumes, and grow.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Medium - Welcome to Medium, a place to read, write, and interact with the stories that matter most to you.
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.