Housing Affordability Calculator

Hacker News

Do you want a housing calculator that: - Is completely client-side - Is easy and straightforward to fill out - Is comprehensive; we include fields such as expenses you budget for which many calculators do not include - Is open source Look no further, because I have a solution for you. I've compiled the formulas that I am using to vet whether or not particular houses are within my means into a webpage that's easily accessible and understandable (and, a little more accurate than ones I've seen online). https://rezach.github.io/house-affordability-calculator/ ----- I post this somewhat in jest - it is fairly trivial to build something like this, but I hope to share it in case others would like to use it or build upon it for their needs.

Visit product View on Hacker NewsJul 30, 2022

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3points

1comments

Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

59%59% 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 · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using, open · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

9%9% 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.

Incorrect prediction on native model

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