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Solve "How to find numbers that add up to a target" once and for all

Hacker News

Solve "How to find numbers that add up to a target" once and for all

I recently came into this problem myself and found the same question has been repeatedly posted online. A common workaround is to use Excel Solver. But it has two major limitations: * It can only handle up to around 70 numbers at a time; * It supports only one target sum at a time. So, I developed a Google Sheets add-on called "Add Up To" in the hope of solving the problem and all similar ones. If you're facing the same challenge, check it out at https://workspace.google.com/marketplace/app/add_up_to/10202... It's completely free for now and may become a paid add-on with a one-off fee in the future when it becomes more mature.

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: google · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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