St
Stupid Simple YouTube Recommendation System
Hacker NewsStupid Simple YouTube Recommendation System
Hi everyone, I was wondering if it would be possible to build a better YouTube recommendation system using only simple heuristics and no ML/Data Science whatsoever. This is the result. I leave you to do judge if it's actually better then Youtube's recommendation system. If you want to browse the code : https://github.com/nassimsoftware/Stupid-Simple-YouTube-Sugg...
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1points
Did not reach leaderboard
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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released42%42% 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 · Missing: mobile apps, ios, personal35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using, code · Missing: mac, agents, macos32%32% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting25%25% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue19%19% 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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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