Br
Bring your own Data: automatic ML (side project)
Hacker NewsBring your own Data: automatic ML (side project)
Share cardActual performance
2points
4comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos75%75% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released53%53% 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, intuitive47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal43%43% 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, podcasting38%38% predicted probability of success on Indie Hackers, 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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
In
In ML Data is not everything – a business perspective55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
In ML Data is not everything – a business perspective
Hacker News2Sudopoint24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Get example data for your next project
Indie Hackerscommitment-side-projectML
ML data annotations and tagging made easy65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
ML data annotations and tagging made easy
Hacker News41Bi
Bifrost Data Search – 1800 image datasets for your next ML project52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Bifrost Data Search – 1800 image datasets for your next ML project
Hacker News3Da
Data Yoshi – Find the Newest Data and ML Jobs56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Data Yoshi – Find the Newest Data and ML Jobs
Hacker News1Au
Automatic Parallelization for Haskell74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Automatic Parallelization for Haskell
Hacker News1Au
Automatic CloudWatch Alarms52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Automatic CloudWatch Alarms
Hacker News1AP
APReF: An Automatic Parallelizer of Recursive Functions for Haskell67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
APReF: An Automatic Parallelizer of Recursive Functions for Haskell
Hacker News2Au
Automatic Installer for ArchLinux ARM51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Automatic Installer for ArchLinux ARM
Hacker News1Au
Automatic initializer methods for Objective-C39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Automatic initializer methods for Objective-C
Hacker News3