In
InverSQL: Build SQL interactively in inverse
Hacker NewsInverSQL: Build SQL interactively in inverse
Since both ML [1] and SQL can be used to select cells from a table, can I convert one to the other? This allows creating SQL in a smart way (select cells -> build SQL, hence the name inverse SQL). Yes. Create a decision tree (an ML predictor) from the cells selected Formulate it as SAT Simplify it Convert to SQL. Demo on streamlit. Love to hear your thoughts and suggestions on this! [1]: ML = machine learning, here I’m using decision trees
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Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, using · Missing: agents, macos, agent41%41% 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, intuitive34%34% 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, podcasting33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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