Learn 10x Faster Than Spaced Repetition with Guided Mnemonics

Hacker News

We've had a lot success in classrooms and the field but explaining how RebilderU's accelerated learning process works online has been difficult. While it does require a new way of thinking, the underlying process is incredibly simple and effective. Check it out here: http://www.rebilderu.com/how-guided-mnemonic-learning-works/ If you have any feedback on the explanation or what doesn't make sense we'd really appreciate it.

Visit product View on Hacker NewsNov 18, 2014

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6points

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Did not reach leaderboard

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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.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, plain · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

29%29% 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, revenue

15%15% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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