+
+

Related Products

  • Qloo
    23 Ratings
    Visit Website
  • Nutrient SDK
    111 Ratings
    Visit Website
  • DXcharts
    28 Ratings
    Visit Website
  • Apify
    1,714 Ratings
    Visit Website
  • pCloud Business
    189 Ratings
    Visit Website
  • SDS Manager
    4 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Highcharts
    123 Ratings
    Visit Website
  • Nasdaq Metrio
    14 Ratings
    Visit Website

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

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Audience

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

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

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

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

PyTorch
Founded: 2016
pytorch.org

Alternatives

Alternatives

Core ML

Core ML

Apple
Create ML

Create ML

Apple
DeepSpeed

DeepSpeed

Microsoft
Deci

Deci

Deci AI
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Deep Learning Supported
Neural Network Supported

Categories

AI Development Supported
Machine Learning Supported
Neural Network Supported

Integrations

AWS Elastic Fabric Adapter (EFA) Not Supported
Amazon EC2 UltraClusters Not Supported
ApertureDB Not Supported
Bayesforge Not Supported
Cleanlab Not Supported
Coiled Not Supported
Daft Not Supported
Fabric for Deep Learning (FfDL) Not Supported
FakeYou Not Supported
Flower Not Supported
GPUonCLOUD Not Supported
Giskard Not Supported
Groq Not Supported
Intel Tiber AI Cloud Not Supported
LiteRT Not Supported
NVIDIA FLARE Not Supported
NVIDIA NGC Not Supported
Sharon AI Not Supported
Voxel51 Not Supported

Integrations

AWS Elastic Fabric Adapter (EFA) Supported
Amazon EC2 UltraClusters Supported
ApertureDB Supported
Bayesforge Supported
Cleanlab Supported
Coiled Supported
Daft Supported
Fabric for Deep Learning (FfDL) Supported
FakeYou Supported
Flower Supported
GPUonCLOUD Supported
Giskard Supported
Groq Supported
Intel Tiber AI Cloud Supported
LiteRT Supported
NVIDIA FLARE Supported
NVIDIA NGC Supported
Sharon AI Supported
Voxel51 Supported
Claim ConvNetJS and update features and information
Claim ConvNetJS and update features and information
Claim PyTorch and update features and information
Claim PyTorch and update features and information