Co
Computed fields for Backbone.Models
Hacker NewsComputed fields for Backbone.Models
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models · Missing: mac, agents, macos81%81% 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.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto81%81% predicted probability of success on BetaList, based on ML models trained on real launch data.
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, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Va
Validating models in Django 1.844%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Validating models in Django 1.8
Hacker News2Dj
Django-spaghetti-and-meatballs – serving up ERDs from django models50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Django-spaghetti-and-meatballs – serving up ERDs from django models
Hacker News3Es
Estimation of flop counts for MXNet models37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Estimation of flop counts for MXNet models
Hacker News1Pr
Probe PyTorch Models36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Probe PyTorch Models
Hacker News2Im
Implementation of DDPM (Denoising Diffusion Probabilistic Models)59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Implementation of DDPM (Denoising Diffusion Probabilistic Models)
Hacker News10Do
Do Models Represent Epistemic Stance?47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Do Models Represent Epistemic Stance?
Hacker News3Karachi Models46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Call girls Karachi
Indie Hackers1$200/moadvertisingOr
Orthogami – Turn voxel models into foldable papercraft61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Orthogami – Turn voxel models into foldable papercraft
Hacker News49La
Lar-JEPA – A Testbed for Orchestrating Predictive World Models33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Lar-JEPA – A Testbed for Orchestrating Predictive World Models
Hacker News2Le
Learn about models of computation interactively61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Learn about models of computation interactively
Hacker News2