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I made an interactive Jupyter Notebook about ciphers

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I made an interactive Jupyter Notebook about ciphers

Just started using this platform and decided I may as well share this and see what people think: https://github.com/TuanaCelik/BrilliantCiphers This is an interactive Jupyter notebook that explains the relation between ciphers and the frequency of letters in an encrypted English text. You can launch the interactive notebook with binder (at bottom of Readme), and play around with the graphs and code. It takes a while to load the first time.. The idea was to design a course on ciphers for people with basic Python knowledge. Let me know what you think!

Visit productView on Hacker NewsDec 15, 2020
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
65%65% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: using, code, plain · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
37%37% 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
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
17%17% 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.

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