Search Results for "machine learning projects"

CSS-Inspiration is a living gallery of modern CSS effects and components that highlights what’s possible with pure CSS and minimal markup. The collection ranges from micro-interactions and loaders to 3D transforms, complex backgrounds, hover states, and text effects, each presented as a small, self-contained demo. Source code is front and center, encouraging developers to study, copy, and tweak snippets for their own projects. Many examples lean on contemporary features—custom properties,...

frontend-park is a collection of engaging frontend projects and experiments, showcasing various web technologies. It includes examples ranging from pose and face recognition using TensorFlow.js to WebRTC-based video calls and Three.js 3D animations. This repository serves as a playground for exploring and learning modern frontend development techniques.

TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization...

...It covers a wide range of topics including animations, layout tricks, transitions, and creative visual compositions. The project is structured as a reference-style showcase where each example isolates a specific technique, making it easy to study and adapt into real projects. Its educational value lies in revealing non-obvious CSS behaviors and encouraging deeper mastery of the styling layer. Overall, css3- serves as a comprehensive learning and inspiration resource for developers seeking to master advanced CSS3 techniques.

Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc. Check out the demos/ directory for real examples running Keras.js in VueJS. Library version compatibility, Keras 2.1.2.