Search Results for "visual neural networks"
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Showing 24 open source projects for "visual neural networks"
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ml.js
Machine learning tools in JavaScript
This library is a compilation of the tools developed in the mljs organization. It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add to your dependencies only the libraries that you need, as they are usually published to npm more often. We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find. -
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NanoNeuron
NanoNeuron is 7 simple JavaScript functions
Nano-Neuron is a didactic project that reduces the idea of a neuron to a handful of tiny JavaScript functions so learners can see “learning” in action without heavy frameworks. It demonstrates how a scalar input can be linearly transformed with a weight and bias, then adjusted via gradient updates to fit a simple mapping such as Celsius-to-Fahrenheit conversion. The code emphasizes readability over performance, inviting you to step through calculations and watch parameters converge. Because... -
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city-roads
Visualization of all roads within any city
city-roads is a data visualization and mapping project that renders street networks of cities as vector paths, offering an interactive, zoomable experience that highlights how cities are stitched together by their road infrastructure. It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. -
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Transformer Explainer
Learn How LLM Transformer Models Work with Interactive Visualization
...The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward networks. Users can observe how attention weights change as the model predicts the next token, offering insight into how transformer architectures capture relationships between words. ... -
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GNNPCSAFT Web App
Smart Thermodynamic Modeling with Graph Neural Networks
The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. -
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Pandora Open
Open Source Monitoring System for performance and availability.
Pandora OPEN is a high-performance, 100% open-source monitoring ecosystem, born as the independent evolution of the Pandora FMS community branch after version 777. Licensed under GPLv2, it provides a modular and sovereign platform for supervising networks, servers, and applications without commercial dependencies. It features multi-platform agents, remote monitoring (SNMP, WMI, HTTP), GIS maps, and advanced visual dashboards. Entirely maintained by the community on GitHub, it ensures total transparency, technical flexibility, and absolute freedom for system administrators. -
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GNNPCSAFT Chat
Chatbot with GNNPCSAFT
The GNNPCSAFT Chat is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, you can chat with LLM models (Gemini or Ollama) with GNNPCSAFT tools, allowing you to ask questions about the PC-SAFT parameters of various compounds, predict thermodynamic properties, and get insights into the GNNPCSAFT's performance. -
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ml5.js
Friendly machine learning for the web
A neighborly approach to creating and exploring artificial intelligence in the browser. ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies. -
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Teachable Machine
Explore how machine learning works, live in the browser
Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge. Users can provide example images for different categories, and the system trains a model that learns to classify those inputs in real time. The project is built using web technologies and the TensorFlow.js ecosystem, enabling machine learning models to run locally within the browser environment. ... -
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neurojs
A JavaScript deep learning and reinforcement learning library
...It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and reinforcement learning methods such as deep Q-networks and actor-critic algorithms. Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks. -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. Let’s break down a CNN into its basic building blocks. ... -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic... -
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VivaGraph
Graph drawing library for JavaScript
VivaGraphJS is a powerful, high-performance graph drawing library for JavaScript that enables developers to visualize complex networks directly in the browser or in Node.js environments. It is designed for speed and scalability, handling large graph datasets with smooth rendering and interactive capabilities such as dragging nodes and zooming. The library supports multiple rendering backends including SVG, WebGL, and Canvas, allowing developers to choose the best balance of performance and visual fidelity for their use case. ... -
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DeepTraffic
DeepTraffic is a deep reinforcement learning competition
...The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an educational competition associated with MIT’s deep learning courses, encouraging students and researchers to experiment with reinforcement learning techniques. The environment provides a coding interface where users can design neural network architectures and tune hyperparameters while observing their agent’s performance in a visual simulation. -
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Synaptic
Architecture-free neural network library for node.js and the browser
...If you have no prior knowledge about Neural Networks, you should start by reading the provided guide. -
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Machine-Learning-Flappy-Bird
Machine Learning for Flappy Bird using Neural Network
Machine-Learning-Flappy-Bird is an educational machine learning project that demonstrates how an artificial intelligence agent can learn to play the Flappy Bird game using neural networks and evolutionary algorithms. The system simulates a population of birds that each possess their own neural network, which acts as a decision-making controller during gameplay. The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. ... -
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Visual NMS
Visual Network Management System
VisualNMS is a network management system with powerful visualisation features due to its vectorial based rendering (SVG). It is built using perl, javascript, SVG, HTML. It includes Layer 2 autodiscovery based on LLDP and other discovery protocols (Cisco's CDP, Extreme Networks' EDP, etc.). Other features include: real time SVG graphs on links, web2cli engine (AJAX to Telnet/CLI), editable maps, auto layout (based esentially on GraphViz), VLAN mapping (work in progress) based on SNMP. -
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ConvNetJS
Deep learning in Javascript to train convolutional neural networks
ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. ... -
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This project intends to create a bacteria simulator framework, with some realistic bacteria control methods based on chemical signaling, simple sensors, motors and neural networks. The bacteria will evolve in a genetic algorithm environment.
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This project is about creating A Web-based collaborative development environment that enables users of Web 2.0 communities and Web-based social networks to create and share interactive applications collaboratively.
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Turn-based strategy game for developers/technical experienced users, based on neural networks, algorithmic programming languages and other techniques.
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A web based Media and Entertainment server system, designed for use on lans and home networks. Current formats supported are MP3 and OGG Vorbis. Many more audio and video formats will be available. New features will be added shortly. See Home Page.
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Network Topology
Network monitoring
Visual tool to actively monitor networks. Compatible with SNMP.
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