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Hooktheory, Music theory for songwriting

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Hooktheory, Music theory for songwriting

Hooktheory is a pretty unique approach to music theory and songwriting. Most books in this area tend to use examples from classical music, while all our examples draw from popular songs you hear on the radio. The book also uses the Theorytab format we developed to let you see the chords/melody in sync with the music while it plays. Theorytabs associate colors with musical function and are more accessible to folks who don't know conventional sheet music. We skip a lot of the basics (scales, key signatures, notation, etc.) that most people associate with music theory (and find rather dull) and go directly into looking at which chords go together best and why (no prior music theory knowledge is required) The first book covered mostly songs in major. The sequel we are releasing today covers minor harmony and a whole lot more. http://www.hooktheory.com/music-theory-for-songwriting Our article series "I analyzed the chords to 1300 songs for patterns, this is what I found" was #1 on hackernews a few years back and is very much in the spirit of the book (though the book goes a lot farther, of course). http://www.hooktheory.com/blog/i-analyzed-the-chords-of-1300-popular-songs-for-patterns-this-is-what-i-found/ Hope you like it!

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Indie HackersFits the IH revenue-focused audience · Strong signals: songs · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
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TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
33%33% 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
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1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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