ConvNetJS 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.

Integrations

API:
Yes, ConvNetJS has an API
No Integrations at this time

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Company Details

Company:
ConvNetJS
Website:
cs.stanford.edu/people/karpathy/convnetjs/

Media

ConvNetJS Screenshot 1
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Product Details

Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support

ConvNetJS Features and Options

Deep Learning Software

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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