Teckstack
Question-based learning for web developers
It seems like all learning materials that exist are either skill-based (i.e. coding challenges with Hackerrank), or course-based (Pluralsight, Udemy). Teckstack is designed for those pursuing knowledge mastery.
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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