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Predictobot, predictive modeling made easy

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Predictobot, predictive modeling made easy

Predictobot lets you build a predictive model without any programming. You upload a spreadsheet of data, specify the column you want to predict, and it automatically builds a predictive model for a regression or classification problem based on the other columns. You download a new spreadsheet, with the model right in the Excel formulas. That lets you make predictions going forward. Other services like this are really aiming at helping programmers to build models. I wanted to make something that a regular non-programmer could use, to get insight into their data. It is open for registration now with no invite needed (unless I get a big rush), so register now and have a play. There are some examples on the site at https://www.predictobot.com/examples/ with little explainer videos. You can play with the results directly, see https://www.predictobot.com/examples/3/ for instance. Click on the little squares and you can interact with the model. Your first 5 models are free during beta. Your first model will be free after the beta. Upload size is limited to 75MB (since it is for doing spreadsheet scale data, not big data.) I'd love to hear your comments, good or bad.

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
84%84% 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: model, new, models · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
60%60% 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
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
40%40% 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
15%15% 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.

Correct prediction on native model

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