Sp
Spectral – Visualize, explore, and share code in Python/JS/TS
Spectral – Visualize, explore, and share code in Python/JS/TS
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →61%61% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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