PyTorch might be a bit more popular than jQuery. We know about 133 links to it since March 2021 and only 102 links to jQuery. 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 / 19 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 / 3 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
To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 27 days ago
With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 1 month ago
Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 2 months ago
8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months 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.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
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.