The C++ Guide for JavaScript Developers

Hacker News

Hi Hacker News! I'm Oscar! I do a lot of react native and web development, therefore I mostly code in JavaScript, however some of the new technologies coming up such as web assembly and the react-native JSI require knowledge of low level languages. In order to leverage this new tech I had to learn C++ and it was not an easy path, a lot of the documentation and knowledge out there is way too hard or in depth for my purposes, I just want to use C++ as fast as I can to achieve my own goals. Therefore I want to make the path easier for other developers, in just a couple of hours I'm trying to cover the most interesting parts of C++, the 20% that will allow you to achieve 80% of what is possible. Course is completely free, hosted on youtube, if you like it I would ask you to subscribe or to follow me on twitter! feedback is of course welcome! https://www.youtube.com/watch?v=YOsCv4_vMgo&list=PLanS_SVm5swgrFrqo-NTITZxud4KRmZgB

Visit product View on Hacker NewsSep 13, 2021

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1points

Did not reach leaderboard

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

87%87% 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: hacker news, ide, io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

11%11% 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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