Based on our record, jQuery should be more popular than Keras. It has been mentiond 102 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.
When I was building a quick frontend to the LLM game, I used jQuery to quickly whip out a prototype. Only after I was happy with it, I ported the code to the modern DOM API. As a result, I totally removed the dependency on jQuery. This whole experience makes me wonder, do people still use jQuery, in this age of frontend engineering? I took some time over the weekend to port one of my old jQuery plugins. This is... - Source: dev.to / 18 days ago
Whenever the number of items increased, the browser became slow, sometimes even unresponsive. At first, we thought it was a server issue or maybe too much data. But no — the problem was hiding inside a small line of jQuery. - Source: dev.to / about 2 months ago
Ah, jQuery — the library that powered a generation of web apps. - Source: dev.to / 2 months ago
Then we have callbacks, which were popularized by AJAX calls. Back then, with jQuery, we could define handlers to deal with both success or failure cases. For instance, let's say we want to fetch the HTML markup of this blog (skipping error failure callback for brevity), we do. - Source: dev.to / 2 months ago
One of them is JQuery created by John Resig. The library addresses extremely-frustrating issues related to cross-browser compatibility that existed at the time. To this day, it remains the most widely used JavaScript library in terms of actual page loads. - Source: dev.to / 5 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
React Native - A framework for building native apps with React
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.
Babel - Babel is a compiler for writing next generation JavaScript.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
OpenSSL - OpenSSL is a free and open source software cryptography library that implements both the Secure Sockets Layer (SSL) and the Transport Layer Security (TLS) protocols, which are primarily used to provide secure communications between web browsers and …
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.