Pi

Piano Gym - Spaced Reptition In Browswer For MIDI Pianos

Hacker News

Piano Gym - Spaced Reptition In Browswer For MIDI Pianos

Hi there! My name is Logan, and I’m the creator of website Piano Gym! https://pianogym.com You can see a quick demo here: https://www.youtube.com/watch?v=faxNDhOjlh4 Piano Gym is a free website where anyone can use a real Piano to learn music theory and performance in the context of actual sheet music. It uses different types of flash card tools to teach topics, and all of it is managed for you using spaced repetition. You just have to show up and do your reps! Piano Gym provides courses and lessons using the Mayron Cole Piano Method. Currently we have - 4 levels - 128 lessons - 214 pieces of sheet music - 384 flash cards Educators and learners can also create their own content too! The overall goal is to support learners in completing their daily reps through deliberate practice while having fun! I’ve been working on Piano Gym for a long time to make something that can grow with its community. I would love the chance to have anyone interested sign up and try it out! Piano Gym is very strongly in beta, and on its way to being fully released soon! We’re on Discord: https://discord.gg/WFbc45MF3x Instagram: https://instagram.com/Piano_Gym Reddit: https://reddit.com/r/PianoGym Twitch: https://twitch.tv/piano_gym Twitter: https://twitter.com/PianoGym YouTube: https://www.youtube.com/channel/UCeYGyfREMqPovx-lxRYPkdg You can watch me use Piano Gym on Twitch. I like to stream myself using Piano Gym, and streaming myself programming the website! In this way you can actually watch Piano Gym grow. We have a Patreon where you can donate money to help me focus on this full time! (It would be very cool to work on this 100% full-time!) https://patreon.com/pianogym Lastly, since this is Hacker News, I can’t do this all on my own, so if anyone is interested in helping a free website grow, please feel free to reach out directly. I’d love to chat :) If you made it this far, thank you for reading and I hope to see you at the gym!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
94%94% 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: hacker news, ide, io · Missing: https docs, excited, just released
73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, context, using · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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