Categories |
|
---|---|
Website | witheve.com |
Categories |
|
---|---|
Website | jupyter.org |
Based on our record, Jupyter seems to be a lot more popular than Eve. While we know about 202 links to Jupyter, we've tracked only 7 mentions of Eve. 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.
There's also https://github.com/mech-lang/mech . That too seems to be getting close to hiatus. It's a bit of a shame since it seems like quite a nice paradigm for some stuff like GUIs, interactive stuff, and discrete event simulation, but I suppose the paradigm is both a bit obscure and different enough from everything else that it becomes a "boil the ocean" situation where one or a few people try and hack away... - Source: Hacker News / 5 days ago
Interesting perspective. It reminds me of Eve [1], which was all the rage over here a few years ago. [1] https://witheve.com/. - Source: Hacker News / 9 months ago
You can read more about it here: http://witheve.com. Source: 11 months ago
I helped with the Eve language, which was an attempt down this path (https://witheve.com) After that project ended I started working on my own attempt (https://GitHub.com/mech-lang/mech). Someone else posted a link to futureofcoding.org, which is a community that works on these types of projects. You can find a lot more there. - Source: Hacker News / about 1 year ago
Some langs have been made more or less like this (ex: http://witheve.com). Source: almost 2 years ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 25 days ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 26 days ago
They make it easy to launch multiple case-by-case data science projects and run your local code right from Jupyter Notebook. - Source: dev.to / about 2 months ago
Talking to some colleagues and friends lately gathering some ideas of a nice Machine Learning project to build, I’ve seen that there’s a gap of knowledge in terms of how do one exactly uses a Machine Learning model trained? Just imagine yourself building a model to solve some problem, you are probably using Jupyter Notebook to perform some data clean up, perform some normalization and further tests. Then you... - Source: dev.to / 3 months ago
This year I decided to commit to a set of tools on day 1 (Polars and Jupyter) and use them for the whole challenge. It seemed silly to do a whole new meandering walkthrough, so instead I'll highlight a few things that stuck out after finishing the challenge and sitting on it for a few days. Here we go! - Source: dev.to / 3 months ago
Observable Notebooks - The portfolio and technical blog of Chris Henrick – provider of professional web development, data visualization, GIS, mapping, & cartography services.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Calculist - The open-source, web-based thinking tool that facilitates effective thinking for solving problems.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Deco IDE - Best IDE for building React Native apps
Google BigQuery - A fully managed data warehouse for large-scale data analytics.