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Description
ConvNetJS is a JavaScript library designed for training deep learning models, specifically neural networks, directly in your web browser. With just a simple tab open, you can start the training process without needing any software installations, compilers, or even GPUs—it's that hassle-free. The library enables users to create and implement neural networks using JavaScript and was initially developed by @karpathy, but it has since been enhanced through community contributions, which are greatly encouraged. For those who want a quick and easy way to access the library without delving into development, you can download the minified version via the link to convnet-min.js. Alternatively, you can opt to get the latest version from GitHub, where the file you'll likely want is build/convnet-min.js, which includes the complete library. To get started, simply create a basic index.html file in a designated folder and place build/convnet-min.js in the same directory to begin experimenting with deep learning in your browser. This approach allows anyone, regardless of their technical background, to engage with neural networks effortlessly.
Description
Protégé benefits from a robust network of users from academia, government, and industry, who utilize it to create knowledge-driven solutions across various fields such as biomedicine, e-commerce, and organizational modeling. Its versatile plug-in architecture allows for the development of both straightforward and intricate ontology-based applications. Developers have the capability to connect Protégé's outputs with rule systems or other problem-solving tools, enabling the creation of a diverse array of intelligent systems. Crucially, the dedicated Stanford team, alongside the extensive Protégé community, is readily available to provide assistance. This community actively engages by answering inquiries, contributing to documentation, and developing plug-ins. Furthermore, Protégé's foundation in Java enhances its extensibility, while its plug-and-play environment ensures it serves as a flexible platform for quick prototyping and application development, paving the way for innovative projects and solutions.
API Access
Has API
API Access
Has API
Integrations
Qwen3-Omni
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ConvNetJS
Website
cs.stanford.edu/people/karpathy/convnetjs/
Vendor Details
Company Name
Center for Biomedical Informatics Research
Country
United States
Website
protege.stanford.edu/
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization