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My first web app trains your ears

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My first web app trains your ears

Hi HN, I've been taking guitar lessons and one thing that is recommended to most musicians is ear training - where two different notes are played and you must identify the number of steps between the notes. My app, Earbuilder, should help with that process. You can find it here: http://www.earbuilder.com/ It's my first web app, and my first real foray into JavaScript. You can take a look at the source and you'll see that it's pretty poorly structured, but I've picked up a book and hopefully things will improve with my second web application. Please let me know if you have any comments, suggestions, or hate because I'm looking to improve this over the coming weeks!

Visit productView on Hacker NewsFeb 13, 2013
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
72%72% 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: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: notes · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
20%20% 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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