I'm writing a book to teach intermediate web app programming

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Hey HN — I've done a couple Show HN's for my first book, Hello Web App (http://hellowebapp.com): My first Kickstarter: https://news.ycombinator.com/item?id=7699291 Launch of Hello Web App: https://news.ycombinator.com/item?id=9329942 Since launch, Hello Web App has had over 1,000 readers and currently has a 5-star rating on Amazon. Yay! I'm now finishing up a follow-up book, which is fundraising/taking pre-orders on Kickstarter now. Hello Web App: Intermediate Concepts covers topics such as: * Adding payments (using Stripe) * Adding an API * Adding user-uploaded images, and using a library to resize/edit those images automatically. * Database design * Intermediate form stuff * And a bunch more. If all goes to plan, will be released to Kickstarter backers in December. It's a followup for anyone who read my original book, or anyone with a basic understanding of Django web development and wants to build out their app (like anyone who has gone through the official Django tutorial or the great DjangoGirls tutorial). If you're interested in the new book or both the old and new book, there are Kickstarter rewards covering both. :) Campaign link: https://www.kickstarter.com/projects/1868398473/hello-web-app-intermediate-concepts (Oh and watch the video because I make this face and it's slightly terrifying/hilarious: http://imgur.com/WDiDwYq) I LOVE talking process and answering any and all questions, so if anyone has questions about how I taught myself programming, launching my startup, how I self-published a book, etc., I'll be here to chat! Thanks HN. :)

Visit product View on Hacker NewsSep 17, 2015

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

90%90% 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: user, stripe, new · 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, 000, io · Missing: https docs, excited, just released

71%71% 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

45%45% 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

44%44% 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

17%17% 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, reward · Missing: web3, crypto, cryptocurrency

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

Incorrect prediction on native model

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