Nativelaunch.dev
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What is Nativelaunch? ExpoLaunch is a blazing-fast and fully extensible Expo template that helps you build beautiful, production-ready React Native apps โ from MVPs to polished SaaS products. Whether you're launching a side project, building a mobile-first business, or experimenting with new ideas, ExpoLaunch helps you move faster.
What You Get ExpoLaunch is more than a boilerplate โ it's a complete demo application you can run, explore, and extend.
You'll get a fully functional Notes App that includes:
โ Onboarding flow with animated slides โ Google, Apple, and Magic Link authentication via Supabase โ Notes list, detail, and edit screens. Notes and images stored in Supabase โ Persistent local storage (MMKV) + optional Supabase sync โ Seamless navigation with expo-router โ Dark mode support โ Clean TypeScript-first codebase โ Beautiful UI built with Tailwind and NativeWind โ Smooth UI transitions powered by Reanimated โ In-app subscriptions via RevenueCat and StoreKit โ Analytics integrations (Amplitude, PostHog, etc.) โ Monitoring with tools like Sentry โ Internationalization using JSON translation files
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Nativelaunch.dev's answer
ExpoLaunch is a production-ready starter template for building modern mobile apps with Expo and React Native. Unlike many boilerplates, it provides a clean architecture, pre-integrated analytics (Google Analytics, Sentry), subscriptions (RevenueCat), authentication (Supabase), and a polished UI built with Tailwind and reusable components โ all optimized for fast startup and real-world usage.
Nativelaunch.dev's answer
ExpoLaunch saves weeks of setup time by offering a well-structured codebase that handles the most common challenges in mobile app development: authentication, subscriptions, analytics, localization, error tracking, and theming. It's not just a UI kit โ it's a solid foundation to launch your product faster and scale with confidence.
Nativelaunch.dev's answer
Our primary audience includes indie developers, solo founders, and small teams who want to build and launch cross-platform mobile apps efficiently without reinventing the wheel. Whether you're building a SaaS MVP or a mobile side project, ExpoLaunch gives you a strong head start.
Nativelaunch.dev's answer
Nativelaunch.dev's answer
ExpoLaunch was created out of necessity while building Money+, a real-world personal finance app. I needed a robust, well-structured mobile app foundation with authentication, subscriptions, analytics, and a modern UI โ but existing templates were either incomplete or outdated. So I built my own production-ready setup, refined it through real use, and decided to offer it as a premium template for developers who want to skip boilerplate and focus on building.
Nativelaunch.dev's answer
Money+ โ a personal finance app available on the App Store, built entirely with ExpoLaunch.
Based on our record, TensorFlow should be more popular than Nativelaunch.dev. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
It includes Supabase Auth, RevenueCat subscriptions, push notifications (OneSignal), CI/CD with GitHub Actions or EAS, and full docs. I originally shared it a month ago (as ExpoLaunch), got a lot of feedback, and now improved it a lot โ including SDK 53, new architecture, and better docs. https://nativelaunch.dev. - Source: Hacker News / 10 months ago
The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 4 months ago
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 3 years ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 4 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 4 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 4 years ago
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