Tr
Training classifiers with Create ML – fruits, flowers, xray, sentiment
Hacker NewsTraining classifiers with Create ML – fruits, flowers, xray, sentiment
Share cardActual performance
5points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto53%53% 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, personal46%46% 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, podcasting32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Runlog54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
ML training monitor
Indie Hackers1aiTr
Training ML model on 4 datasets at once52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Training ML model on 4 datasets at once
Hacker News2Mo
Monitor ML model training on mobile42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Monitor ML model training on mobile
Hacker News7Gr
Graphsignal – ML profiler to speed up training and inference65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Graphsignal – ML profiler to speed up training and inference
Hacker News16Su
Supamodel -- monitor ML training sessions on your iPhone36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Supamodel -- monitor ML training sessions on your iPhone
Hacker News2An
An annotation tool for ML and NLP63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
An annotation tool for ML and NLP
Hacker News76An
An annotation tool for ML and NLP63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
An annotation tool for ML and NLP
Hacker News5Js
Jsonnet Training42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Jsonnet Training
Hacker News1Ea
Ear Training Exercise63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Ear Training Exercise
Hacker News2Kibana Training35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
kibana training, kibanaonline training, kibana tutorial
Indie Hackerscommitment-full-time