Programming Hub – Code learning made fun

Hacker News

I am new to this community and happy to be here. I am the maker of an app called Programming Hub that makes it easy for beginners to start learning programming languages. It is also useful to practice programming and brush up skills to become interview ready. I have seen a lot of people looking for kickstarts on learning different programming languages or wanting to prepare for coding interviews. This app is my attempt to solve this problem. The app has been recognised by Google as - Google Play's Editor's Choice Google's "Best of the Best" of 2017 Recently, we have revamped our app and I am looking for feedback. Android app link - https://play.google.com/store/apps/details?id=com.freeit.jav... iOS app link - https://itunes.apple.com/us/app/programming-hub/id1049691226 Thanks.

Visit product View on Hacker NewsJan 9, 2019

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5points

2comments

Did not reach leaderboard

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

91%91% 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.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

22%22% 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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