Based on our record, Composer should be more popular than Keras. It has been mentiond 143 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.
There is also no requirement to follow the PHP-FIG standards. The best thing that is build because of those standards is Composer. The most plugins I downloaded while writing use composer. The problem is that the plugins ship with their own vendor directory. While the standard is to have one vendor directory for the whole project. This results in different packages with the same or different version of it in the... - Source: dev.to / about 2 months ago
“Extensions are now very close to being like packages; they basically look like Composer packages. It’s still open to discussion whether PIE will be part of Composer someday. It’s not decided yet, but I hope it will be,” Roman added. - Source: dev.to / about 2 months ago
Dependencies are managed by Composer (like npm, cargo, etc) for more than 10 years now. https://getcomposer.org. - Source: Hacker News / about 2 months ago
Composer and Packagist have become key tools for establishing the foundations of PHP-based applications. Packagist is essentially a directory containing PHP code out of which Composer, a PHP-dependency manager, retrieves packages. Their ease of use and exceptional features simplify the process of importing and managing own and third-party components into our PHP projects. - Source: dev.to / 3 months ago
Simplicity: Getting started is a breeze—install via Composer, define some routes, and you’re off. Scaling up? Add middleware or libs like Twig or Eloquent as needed. - Source: dev.to / 3 months ago
The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / about 1 month ago
If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / 7 months ago
At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / 8 months ago
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 12 months ago
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 1 year ago
jQuery - The Write Less, Do More, JavaScript Library.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
React Native - A framework for building native apps with React
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Babel - Babel is a compiler for writing next generation JavaScript.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.