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LexPrep – reproducible lexical preprocessing for research experiments
LexPrep – reproducible lexical preprocessing for research experiments
I built this to solve reproducibility issues in research pipelines. Would love feedback on architecture. If you find it interesting, a GitHub star would help visibility
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Launch Intel predictions
Analyze your own launch →63%63% predicted probability of success on Product Hunt, 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 AppSumo, based on ML models trained on real launch data.
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
25%25% 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.
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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