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Learn Algorithms by Solving Challenges
Hacker NewsLearn Algorithms by Solving Challenges
I think people can learn Algorithms by solving programming challenges, so I created a (beginner) tutorial for learning Recursion: http://www.learneroo.com/modules/71/nodes/398 I also made tutorials on Trees & Graphs and Sorting: http://www.learneroo.com/modules/32/nodes/227 http://www.learneroo.com/modules/4/nodes/15 I'm interested in hearing feedback on this approach.
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Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released77%77% 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 · Missing: mobile apps, ios, personal52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos28%28% 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, intuitive27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue14%14% 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, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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