An
Antimander – Optimize Congressional Districts with Genetic Algorithms
Antimander – Optimize Congressional Districts with Genetic Algorithms
Share cardActual performance
68points
50comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →84%84% 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.
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
24%24% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Sc
Scipy.optimize.linear_sum_assignment with wings61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Scipy.optimize.linear_sum_assignment with wings
Pr
Prisma Optimize56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Prisma Optimize
Micros - StackTracker26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Supplement smart, optimize you
ReadMeFixi36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Optimize READMEs. Instantly.
FA
FAQ.camp – a FAQ builder with functions to optimize your FAQ52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
FAQ.camp – a FAQ builder with functions to optimize your FAQ
Pr
Prepform – AI and spaced-repetition to optimize learning43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Prepform – AI and spaced-repetition to optimize learning
FundStory50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Optimize your funding story
op
optimize your css with purgecss69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
optimize your css with purgecss
Op
Optimize Databricks SQL73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Optimize Databricks SQL
Clearscope48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Optimize your content for SEO