Kyso – Publish Your Jupyter Notebooks as Blog Posts

Hacker News

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 https://kyso.io/vanaurum/algorithmic-portfolio-optimization https://kyso.io/Don/a-journey-to-the-tip-of-neural-networks https://kyso.io/waldohiding/twitter Happy to hear any and all feedback!

Visit product View on Hacker NewsJun 14, 2018

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Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, visual, code · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: including · Missing: supports, reddit linkedin, podcasting

40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

23%23% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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