Li

Live Twitch Demo at 2pm – Monitor ML Models in Sagemaker with Fiddler

Hacker News

Live Twitch Demo at 2pm – Monitor ML Models in Sagemaker with Fiddler

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
72%72% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models · Missing: mac, agents, macos
65%65% 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 released
59%59% 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
46%46% 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, personal
44%44% 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, podcasting
23%23% 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, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

De
Demo of using DVC and MLFlow for ML experiments38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Demo of using DVC and MLFlow for ML experiments

Hacker News1
Ef
Efemarai – Visualizing and debugging ML models71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Efemarai – Visualizing and debugging ML models

Hacker News8
Li
Live demo of WebEngage49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Live demo of WebEngage

Hacker News2
ML
ML-Powered Search Demo75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ML-Powered Search Demo

Hacker News2
CU
CUGA – Configurable Generalist Agent (HuggingFace Live Demo)47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

CUGA – Configurable Generalist Agent (HuggingFace Live Demo)

Hacker News1
Runlog
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 Hackers1ai
ML
MLSentinel – monitor ML models and catch failures early63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

MLSentinel – monitor ML models and catch failures early

Hacker News2
Pa
Pappice live demo in browser via WASM62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pappice live demo in browser via WASM

Hacker News3
Pa
Panini AI – Serve ML/DL Models in Few Minutes47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Panini AI – Serve ML/DL Models in Few Minutes

Hacker News11
Li
Live Demo of Composite Image Retrieval (CIR)59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Live Demo of Composite Image Retrieval (CIR)

Hacker News2