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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

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

About

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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 interested in a beautiful but advanced programming language

Audience

Developers looking for a scientific computing framework for their neural networks and energy-based models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
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 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

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

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

Python
Founded: 1991
www.python.org

Company Information

Torch
torch.ch/

Alternatives

Alternatives

Alternatives

Neural Designer

Neural Designer

Artelnics
Deci

Deci

Deci AI

Categories

Categories

Categories

Integrations

.NET Aspire
Atri Framework
CodeTasty
Decentriq
Edison Analysis
Gemini 1.5 Pro
Gemini-Exp-1206
GroupBy
Jeeva eClinical Cloud
Llama 3
Mistral Large
Neurotechnology AI SDK
New Relic
Overleaf
Pathway
Spacemacs
SwapCode AI
Understand
Unremot

Integrations

.NET Aspire
Atri Framework
CodeTasty
Decentriq
Edison Analysis
Gemini 1.5 Pro
Gemini-Exp-1206
GroupBy
Jeeva eClinical Cloud
Llama 3
Mistral Large
Neurotechnology AI SDK
New Relic
Overleaf
Pathway
Spacemacs
SwapCode AI
Understand
Unremot

Integrations

.NET Aspire
Atri Framework
CodeTasty
Decentriq
Edison Analysis
Gemini 1.5 Pro
Gemini-Exp-1206
GroupBy
Jeeva eClinical Cloud
Llama 3
Mistral Large
Neurotechnology AI SDK
New Relic
Overleaf
Pathway
Spacemacs
SwapCode AI
Understand
Unremot
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