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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

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

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 an deep learning API solution to minimize the number of user actions required for common use cases

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

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

Review this Software

Reviews/Ratings

Overall 5.0 / 5

Pros & Cons from Real Users

Pros

  • I mostly code in Python, so using Keras for my deep learning needs wasn't too hard to get used to, given the abundance of documentation and ease of writing modular code with its API.

Cons

  • Keras only has high level APIs, unlike Tensorflow, which has both high and low level support.

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

Keras
United States
keras.io

Alternatives

Alternatives

Deci

Deci

Deci AI

Categories

Categories

Deep Learning Features

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

Integrations

Akira AI
AutoKeras
BentoML
Comet
Dataiku
Gemma 3n
Google AI Edge
Gradient
Horovod
OpenVINO
PaliGemma 2
Polyaxon
Radicalbit
RazorThink
RunCode
Spell
Superwise
Thunder Compute
Zepl
neptune.ai

Integrations

Akira AI
AutoKeras
BentoML
Comet
Dataiku
Gemma 3n
Google AI Edge
Gradient
Horovod
OpenVINO
PaliGemma 2
Polyaxon
Radicalbit
RazorThink
RunCode
Spell
Superwise
Thunder Compute
Zepl
neptune.ai
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