
React
Vue.js
Next.js
Svelte
Angular.io
Tailwind CSS
Node.js
AngularJS
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
React
DeepnoteBased on our record, React seems to be a lot more popular than Deepnote. While we know about 818 links to React, we've tracked only 34 mentions of Deepnote. 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.
Let's start by preparing a sample application that we want to place in a Docker image. This will be a web application created using the React framework and its create-react-app tool. It will generate a code template and configuration, allowing us to focus on the image creation aspects. - Source: dev.to / about 1 year ago
Python integrates seamlessly with machine learning (TensorFlow, PyTorch) and data analytics stacks (Pandas). Node.js integrates better with frontend JS ecosystems like React, Vue, and Next.js. - Source: dev.to / 9 months ago
Dora AI exemplifies this. Allan Murphy Bruun adds, "What makes it different is its context-aware logic stitching that understands user flows beyond just UI elements." By analyzing Figma designs, it generates React code with state management, saving hours in development. - Source: dev.to / 11 months ago
Import { createFileRoute } from "@tanstack/react-router"; Import logo from "../../logo.svg"; Import "../../App.css"; Export const Route = createFileRoute("/_authenticated/")({ component: AuthenticatedRoute, }); Function AuthenticatedRoute() { return (- Source: dev.to / 12 months ago![]()
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One inspiring example is a developer building a "Todoist Clone" using a combination of React, Node.js, and MongoDB. The developer tapped into open source libraries and community support to create a highly responsive task management application. This project underscores how indie hackers can achieve rapid development and adaptation with minimal budget โ a theme echoed in several indie hacking success stories. - 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
Vue.js - Reactive Components for Modern Web Interfaces
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Next.js - A small framework for server-rendered universal JavaScript apps
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.
Svelte - Cybernetically enhanced web apps
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.