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I wrote a simple book on Git
Hacker NewsI wrote a simple book on Git
Hi guys! I wrote a book on Git, that would help beginners get started with Git over a weekend. You can read a free chapter here - https://www.sitepoint.com/git-branching/ You can find the book here - https://www.sitepoint.com/premium/books/jump-start-git (You may access the book through a free 14 day trial here: https://www.sitepoint.com/premium/products/Z2lkOi8vbGVhcm5hYmxlL1Byb2R1Y3QvMg) I would request you to go through the sample chapter and let me know what you think. Thanks!
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting58%58% 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 · Missing: https docs, excited, just released50%50% 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, intuitive48%48% 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, personal42%42% 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, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos13%13% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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