stackii
Library of resources for indie hackers
I've always enjoyed reading posts about the tech/tool stack used by indie hackers. I guess for me, maybe others as well, learning more about the decisions others make regarding their stack is inspiring.
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Launch Intel predictions
Analyze your own launch →49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
20%20% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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