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About

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. The library allows you to formulate and solve neural networks in Javascript, and was originally written by @karpathy. However, the library has since been extended by contributions from the community and more are warmly welcome. The fastest way to obtain the library in a plug-and-play way if you don't care about developing is through this link to convnet-min.js, which contains the minified library. Alternatively, you can also choose to download the latest release of the library from Github. The file you are probably most interested in is build/convnet-min.js, which contains the entire library. To use it, create a bare-bones index.html file in some folder and copy build/convnet-min.js to the same folder.

About

Neurons are the basic unit of the neural network. They can be connected to another neuron or gate connections between other neurons. This allows you to create complex and flexible architectures. Trainers can take any given network regardless of its architecture and use any training set. It includes built-in tasks to test networks, like learning an XOR, completing a Discrete Sequence Recall task or an Embeded Reber Grammar test. Networks can be imported/exported to JSON, converted to workers or standalone functions. They can be connected to other networks or gate connections. The Architect includes built-in useful architectures such as multilayer perceptrons, multilayer long short-term memory networks (LSTM), liquid state machines and Hopfield networks. Networks can also be optimized, extended, exported to JSON, converted to Workers or standalone Functions, and cloned. A network can project a connection to another, or gate a connection between two others networks.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers, professionals and researchers seeking a solution for training deep learning models

Audience

Developers looking for an architecture-free neural network library for node.js and the browser

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

ConvNetJS
cs.stanford.edu/people/karpathy/convnetjs/

Company Information

Synaptic
caza.la/synaptic/#/

Alternatives

Alternatives

Sharky Neural Network

Sharky Neural Network

SharkTime Software
Deci

Deci

Deci AI

Categories

Categories

Integrations

Qwen3-Omni

Integrations

Qwen3-Omni
Claim ConvNetJS and update features and information
Claim ConvNetJS and update features and information
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Claim Synaptic and update features and information