Bigbeans.ai – Fast charge ML learning by practicing problems

Hacker News

Hi HN, We are excited to share with you https://bigbeans.ai — a platform to learn ML/AI by practicing problems. Since ChatGPT’s launch last year, there’s increased funding and interest in ML. We believe every engineer is going to need ML skills to be successful. The best way we learnt ML is by practicing real-world problems. We didn’t find a platform with low friction to do that and hence decided to build it for others in our free time. Give it a go at https://bigbeans.ai We appreciate your thoughts, feedback, and ideas!

Visit product View on Hacker NewsJul 29, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

53%53% 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

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: chatgpt · Missing: mac, agents, macos

37%37% predicted probability of success on Product Hunt, 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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