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Practice where countries are in the world

Hacker News

Practice where countries are in the world

TLDR: Practice where countries are on the world map https://www.samlearns.org/world-map Hello HN, ...I keep making little web apps to practice geography, and since some people here enjoyed the previous version, I thought this one too. It's a simple game loop where you have to either tab or name countries, w/ some varying conditions like zoom levels. Following feedback from last time, I reconsidered almost all of the game systems, fixing quite a few issues (too hard, too easy, too many boring islands, countries recurring often, confusing UX, ...). The stack is ts/vue and geojson, with some python for data crunching; learning algo built on top of FSRS. It's all free, no-ads, no-signup and open source, in case you were wondering. Feedback and ideas welcome! Hope you get something out of this, cheers :)

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75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps, using, open · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: recurring · Missing: arr, mrr, revenue
16%16% 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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