Simon – open-source automated machine learning

Hacker News

Hello HN crowd, I would love to show you open source project I've been working on for the last year or bit more, SIMON ( https://github.com/genular/simon-frontend ) In short, it is an autoML platform, with a primary goal to be used as a knowledge discovery application. This is an initial release of it so you can consider it as heavy beta :) You can check it and read more about it on the project GitHub page, or on the official website ( https://genular.org ) If you wish you can check screenshots of the SIMON here https://genular.org/simon-screenshots/ or watch this demo video I made here https://www.youtube.com/watch?v=Oc_LvH85Uaw (it's not really nicely edited since I had a hard time doing editing on my Linux machine) I also placed an announcement on Product Hunt, if interested: https://www.producthunt.com/posts/simon-2 I would also like to give huge credit to my wife https://twitter.com/TomicAdriana since without her support SIMON would never exist! I wish you all a very nice start of the week, and hope that maybe some of you will find SIMON very useful in your research!

Visit product View on Hacker NewsApr 29, 2019

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: wife · Missing: supports, reddit linkedin, podcasting

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

Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, ide · Missing: https docs, excited, just released

74%74% 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 HuntOn track for Day 1 leaderboard · Strong signals: mac, open · Missing: agents, macos, agent

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

13%13% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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