Au

AutoML state-of-the-art performance on tabular data

Hacker News

AutoML state-of-the-art performance on tabular data

Share card

Actual performance

1points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
57%57% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
38%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, crypto
35%35% 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, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Ontor
Ontor76%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Boost your performance by measuring nervous system state

Indie Hackerscommitment-full-time
Gi
Give a badge to your performance data44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Give a badge to your performance data

Hacker News1
La
Last System State Before OOM49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Last System State Before OOM

Hacker News1
Th
The state of state in the browser55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The state of state in the browser

Hacker News3
Us
Use-async-call – manage the state and lifecycle of async data loading40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Use-async-call – manage the state and lifecycle of async data loading

Hacker News1
Re
Restate – Build understandable backends with state machines54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Restate – Build understandable backends with state machines

Hacker News2
Fl
Flair – State of the art NLP framework on top of pytorch63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Flair – State of the art NLP framework on top of pytorch

Hacker News11
St
State of Mind by State67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

State of Mind by State

Hacker News1
Re
Redux-undo – Simple undo/redo functionality for Redux state containers48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Redux-undo – Simple undo/redo functionality for Redux state containers

Hacker News41
JQ
JQuery selectors performance44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

JQuery selectors performance

Hacker News1