NQ
NQueens problem solved using backtracking in Elixir lang
Hacker NewsNQueens problem solved using backtracking in Elixir lang
Share cardActual performance
19points
7comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released51%51% 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, intuitive50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto37%37% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting21%21% 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, revenue14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Go
Go-dutchflag – An implementation of the Dutch flag problem in Golang37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Go-dutchflag – An implementation of the Dutch flag problem in Golang
Hacker News3Th
The AZ Problem39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The AZ Problem
Hacker News2So
Someone Else's Problem39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Someone Else's Problem
Hacker News1Th
The farmer, wolf, goat and cabbage problem39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The farmer, wolf, goat and cabbage problem
Hacker News1Mo
Monty Hall Problem39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Monty Hall Problem
Hacker News1Wo
Wolf, Goat and Cabbage Problem39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Wolf, Goat and Cabbage Problem
Hacker News1Gu
Guiderail – How I (partly) solved my procrastination problem46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Guiderail – How I (partly) solved my procrastination problem
Hacker News3Ar
Are the Riemann Hypothesis and Navier-Stokes the Same Problem?56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Are the Riemann Hypothesis and Navier-Stokes the Same Problem?
Hacker News7Th
The problem with the epsilon greedy method33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The problem with the epsilon greedy method
Hacker News22Grubl65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The "What's for dinner" problem solved!
Indie Hackerscommitment-full-time