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DataCabinet, Website to Maintain Jupyter Notebooks in the Cloud

Hacker News

DataCabinet, Website to Maintain Jupyter Notebooks in the Cloud

http://datacabinet.systems DataCabinet is a website to maintain conda environments directly on the cloud and access these environments through Jupyter notebooks. It also offers other useful features like sharing and authentication/authorization. Find detailed usage documentation: https://datacabinet.github.io/ Your feedback would be invaluable as we stabilize and add new features to the product. Here are some access codes to activate the beta: 'y2OdwyOmSb', 'RgcXyBdWA9', 'HnHoCMmbHb', '44cdEazOFl', 'btyqZfxcEz', 'kSm7K8bcsf', 'wFrgedzY8D', 'OfbmB9CqIC', 'qZFbrTqTnM', 'DsDo2dsyU7', 'nGHeiW1aTG', '2z83eGo9t5', 'TXDYzUSOkR', 'qGJElb1ulm', 'f1jORN7Hfz', 'kr7PnQz6op', 'mBeOBrX97D', 'NY8cCWIsT2', '3e5qj4qQJI', 'SsmL2231Qh', 'Yrel78TGB9', 'O3LLe5jTxj', 'rTIih3HxDU', 'G9AOXOeUsL', 'b8GyW2AiRf', 'Wf5baiO5MU', '2XjDyfnFbF', 'jAuNjtK1io', 'X1UwmhKx9i', 'GFtBN2CjGo', 'rwaGLh63Cb', 'gsgublZnkz', 'GPO5dMzuJ5', 'tHbiuG7pYe', 'nKuZCL8pYn', 'hAKjwy1tnb' . If these run out, please sign up at http://datacabinet.info and we will send you more access codes if needed. If you face any trouble, please write to us at info@datacabinet.systems or join our slack channel: https://slackpass.io/datacabinet .

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3points
2comments
Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, new, code · Missing: mac, agents, macos
78%78% 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.
Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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