examples
Flutter
Our great sponsors
examples | Flutter | |
---|---|---|
143 | 1,203 | |
7,742 | 161,649 | |
1.2% | 0.8% | |
6.2 | 10.0 | |
21 days ago | 6 days ago | |
Jupyter Notebook | Dart | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
examples
-
My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
-
Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
-
Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
-
Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
-
MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
-
🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
-
GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
-
🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
-
Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
Flutter
-
Show HN: Shorebird 1.0, Flutter Code Push
[3]: https://github.com/flutter/flutter/tree/master/packages/flut...
-
3D and 2D: Testing out my cross-platform graphics engine
Thanks - that link does not appear to be open access, anyways I don't think I've seen it. I'm familiar with Flutter at a high-level (Kevin Moore gave a great talk on it at Wasm I/O), and I think other than requiring users to work in Dart, it is probably one of the most powerful ways to do cross-platform UI today.
Worth noting that their original GPU backend was Skia, and now they are retooling around Flutter GPU (Impeller)[0], which is kind of designed similarly as an abstract rendering interface over platform-specific GPU APIs.
[0]https://github.com/flutter/flutter/wiki/Flutter-GPU
-
Python dev considering Electron vs. Kivy for desktop app UI
If you are considering Electron/React then I would suggest adding Flutter to your list of technologies to consider. It uses Dart (a language similar to C#) and has a lot going for it… relatively quick to get up to speed with, fantastic developer experience (e.g., hot reload, great IDE support, good development tools) and very strong cross-platform support: it generates native iOS, Android, MacOS, Windows and Linux executables. Check it out: https://flutter.dev/
- Lançamento do App Edudu
- Android 12+: Changing wallpaper or dark theme breaks Flutter and Jetpack Apps
- Android 12: Changing wallpaper or dark theme breaks Flutter and Jetpack Compose
-
React Native and Flutter: A Developer's Dilemma
You can find the React Native documentation here and Flutter Documentation here.
-
Ente: Open-Source, E2E Encrypted, Google Photos Alternative
[1]https://github.com/flutter/flutter/issues/55092#issuecomment...
- Reusing state logic is either too verbose or too difficult #51752
-
React Labs: What We've Been Working On – February 2024 – React Compiler
> There is actually a great issue thread on the Flutter GitHub that explains exactly why other solutions do not work correctly when compared to hooks [0]
Interesting. I assume you are referring to this comment in particular -> https://github.com/flutter/flutter/issues/51752#issuecomment... ?
What are some alternatives?
cppflow - Run TensorFlow models in C++ without installation and without Bazel
Introducing .NET Multi-platform App UI (MAUI) - .NET MAUI is the .NET Multi-platform App UI, a framework for building native device applications spanning mobile, tablet, and desktop.
mlpack - mlpack: a fast, header-only C++ machine learning library
flet - Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required.
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
WPF - WPF is a .NET Core UI framework for building Windows desktop applications.
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Uno Platform - Build Mobile, Desktop and WebAssembly apps with C# and XAML. Today. Open source and professionally supported.
Selenium WebDriver - A browser automation framework and ecosystem.
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Quasar Framework - Quasar Framework - Build high-performance VueJS user interfaces in record time