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takarakuji-ai
japanese lottery prediction site
Open-source analytics for Japan’s Numbers3, Numbers4 & Loto6: historical draws, ensemble ML forecasts, SQLite + GitHub Actions pipelines, and a Next.js dashboard (optional Supabase). Made for transparency and reproducible research—not betting advice, not affiliated with any official lottery operator, and not a promise of results. Feedback from data/ML folks especially welcome.
Hi Product Hunt 👋 I’m [Takeshi Kubokawa / @kubocchi.studio], maker of Million
Pocket Orchestra.
I started this project because I wanted a place where lottery draw
data isn’t just “numbers on a page,” but something you can
explore with clear pipelines: historical results, ensemble ML
forecasts, charts, and reproducible workflows (SQLite + GitHub
Actions) instead of a black box.
It focuses on Japan’s public draws (Numbers3, Numbers4, Loto6) and
ships with a Next.js dashboard (optional Supabase) plus Python
tooling. Everything is open source so you can verify how
predictions are produced and extend the models yourself.
Important context: this is for research, learning, and
transparency—not gambling advice, not affiliated with any official
operator, and not a guarantee of outcomes.
🔗 Source: https://github.com/kubokawa-dev/...
I’d love your thoughts—especially if you’re into data science or
OSS: what would you want to see next (better explainability, more
benchmarks, docs for contributors)?
Thanks for checking it out, and happy to answer questions in the
thread!
About takarakuji-ai on Product Hunt
“japanese lottery prediction site”
takarakuji-ai was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #244 on the daily leaderboard. Open-source analytics for Japan’s Numbers3, Numbers4 & Loto6: historical draws, ensemble ML forecasts, SQLite + GitHub Actions pipelines, and a Next.js dashboard (optional Supabase). Made for transparency and reproducible research—not betting advice, not affiliated with any official lottery operator, and not a promise of results. Feedback from data/ML folks especially welcome.
On the analytics side, takarakuji-ai competes within Open Source, Analytics and GitHub — topics that collectively have 281.5k followers on Product Hunt. The dashboard above tracks how takarakuji-ai performed against the three products that launched closest to it on the same day.
Who hunted takarakuji-ai?
takarakuji-ai was hunted by Takeshi Kubokawa. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of takarakuji-ai including community comment highlights and product details, visit the product overview.
Takeshi Kubokawa