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Where do you rank amongst Developers in your city?

Hacker News

Where do you rank amongst Developers in your city?

I'm a student who had trouble finding software developers who were excelling in my city. While it's possible to find developers on platforms like GitHub and LinkedIn, it's hard to find any objective list of those who are thriving in their region. So, I developed GeoGit, an open-source tool that allows users to rank software developers by location. It still needs lots of changes and adjustments, mostly to the ranking algorithm and performance, but for now provides some interesting and useful info on a location's developer scene. I would really appreciate any feedback on any part of the app. I'm new to web development so I'm really eager to improve. Thanks! :) Repo: https://github.com/sheeehy/GeoGit/

Visit productView on Hacker NewsNov 27, 2023
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1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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.

Correct prediction on native model

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