Pi

PinPoint open source geocoder

Hacker News

PinPoint open source geocoder

For the past few months I have been developing this Geocoding engine. It started out as a small Python module to parse out and cleanse address data. The project eventually grew from an address parser to a geocoder. Currently, the geocoder supports only single addresses[aka no intersections]. There is a lot of work to do so please feel free to help out! Here is the link to the git hub: https://github.com/taurenk/PinPointGeocoder I threw together a very crude demo [I mean VERY crude], which only works for New York addresses : www.pinpointgeocoder.com This is my first time releasing any code, so please email me if you have any suggestions/tip/advice at tauren.kristich@gmail.com

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Actual performance

1points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, single · Missing: mac, agents, macos
82%82% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% 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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