Alternatives
Products that do what RMOTR Notebooks – Free Online Data Science Environment does
Hello HN. We're happy to show to the world a platform that we've created to help our students get started with Data Science: https://notebooks.rmotr.com/ We know how hard it is to start working with Data Science tools: setting up local environment, installing dependencies, keeping projects organized, etc. RMOTR Notebooks has Jupyter Lab already preinstalled + the ability to upload datasets. Our platform is now open to everybody for free, and we are thinking about adding paid tiers in the future with better hardware, GPU support, pro features, etc. We've also worked on a…
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Hi HN, We're the founders of https://kyso.io We want to make it really easy to share data-science within teams, and we've started with Jupyter notebooks. We render the notebooks really nicely, so you can embed interactive visualisations like Bokeh, and Plotly plots. Another nice thing is we allow you to hide the code for non-technical readers, so you basically get a beautiful data blog. Look at https://kyso.io/laura/ for some examples. We really want to hear your feedback, let us know what you think!
2017
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Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
2020
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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2019 · hackerrank.com
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Mercury is a perfect tool to share your Python notebooks with non-programmers. - You can turn your notebook into web app. - You can add interactive widgets to your notebook by defining the YAML header. Your users can change the input and execute the notebook. - You can hide your code to not scare your (non-coding) collaborators. - Users can interact with notebook and save they results. - You can share notebook as a web app with multiple users - they don't overwrite original notebook. The demo running at Heroku (free dyno) http://mercury-demo-1.herokuapp.com, at AWS EC2 (t3a.small)…
2022 · github.com
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Hi HN - the founders of kyso here. Kyso (https://kyso.io) is a blogging platform for data science. We render your jupyter notebooks, including all code, interactive visualisations and rich markdown, as awesome data blogs. Upload existing notebooks, import your repos from Github and start brand new Jupyterlab environments in the cloud, all for free. And then publish and share your blogs with the community! Have a look here for a few example posts on our platform: https://kyso.io/jamesle/fifa18…
2018
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2020 · starboard.gg
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Hello Hacker News! We are Rick & Yannick from Orchest (https://www.orchest.io - https://github.com/orchest/orchest). We're building a visual pipeline tool for data scientists. The tool can be considered to be high-code because you write your own Python/R notebooks and scripts, but we manage the underlying infrastructure to make it 'just work™'. You can think of it as a simplified version of Kubeflow. We created Orchest to free data scientists from the tedious engineering related tasks of their job. Similar to how companies like Netflix, Uber and Booking.com…
2020
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Hey HN community! Over the past year, AI copilots like Cursor and Windsurf have fueled a dramatic shift in software engineering workflows. And yet, many technical users in adjacent fields like data science and analytics have been unable to reap the rewards of this revolution. It turns out that the existing tools are a poor match for analytical workloads. Beyond that Cursor and similar tools have very poor support for Jupyter notebooks, data science is a fundamentally different discipline from software engineering and we believe it requires a correspondingly different tool. We're excited to…
Sep 2025 · sphinx.ai
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