Launch Intel
Ba

Bayesian analysis of 703,139 user events (0.037 seconds)

Hacker News

Bayesian analysis of 703,139 user events (0.037 seconds)

TIL: Go is fast, Python is slow. I had no idea how true this was until I built a Bayesian AB testing stats engine in Go, and compared it to python PyMC3 The repo is a python wrapper around our Bayesian-Go stats engine. You can use the repo to compare PyMC3 bayesian analysis to our API (we're about 1500x faster). You can also use the repo as a python entry-point to our API, if you want to build your own AB experimentation tool but use our backend. I'll spend some time on a proper SDK if there is enough interest :)

Visit productView on Hacker NewsMay 12, 2023
Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, 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: user · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
49%49% 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
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Us
User return analysis in Stackoverflow, Insta, H&M53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

User return analysis in Stackoverflow, Insta, H&M

Hacker News4
Ne
Never lose an argument about user events again38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Never lose an argument about user events again

Hacker News1
Ub
Uber for Events54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Uber for Events

Hacker News10
Th
The Tripadvisor of Hackathon Events32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Tripadvisor of Hackathon Events

Hacker News3
We
Webhooks for Supervisor Events35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Webhooks for Supervisor Events

Hacker News1
do
dom events for your WebGL56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

dom events for your WebGL

Hacker News1
Cr
Crowdfunding for Events36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Crowdfunding for Events

Hacker News2
Re
Reserved Seating for Events30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Reserved Seating for Events

Hacker News2
Ev
Events in Florence (ITA and ENG)30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Events in Florence (ITA and ENG)

Hacker News1
Mixpanel Events 2.0
Mixpanel Events 2.041%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Product Hunt
Browse all productsAnalyze your launch