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Show HN - Looking for beta testers/collaborators for www.bookclub.ai

Hacker News

Show HN - Looking for beta testers/collaborators for www.bookclub.ai

Hi, I am working on this website, www.bookclub.ai It help readers find their next book based on their past preferences. It currently has ML-based recommendation system for 'More Like This' and 'Mind-Map' features. I am looking for a few beta testers or collaborators who want to work on early-stage product development, community building or training AI models to solve real-life Natural Language Processing & Computer Vision problems in the book industry. Would love to get some critical feedback. If someone is interested, please reach out to me at 19aditiyadav@gmail.com or +1-206-228-4232.

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, computer, models · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
57%57% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% 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
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
19%19% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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