ConvNetJS vs. Keras Comparison


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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 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 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 Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases
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 Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or 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 5.0 / 5 Read all reviews
	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 Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information ConvNetJS cs.stanford.edu/people/karpathy/convnetjs/	Company Information Keras United States keras.io
Alternatives Microsoft Cognitive Toolkit Microsoft	Alternatives TensorFlow
Neuralhub	PyTorch
TFLearn	AutoKeras
Zebra by Mipsology Mipsology	AWS Deep Learning AMIs Amazon
Deci Deci AI View All	Deeplearning4j View All
Categories Deep Learning Supported Neural Network Supported	Categories Deep Learning Supported Neural Network Supported
	Deep Learning Features Convolutional Neural Networks Supported Document Classification Not Supported Image Segmentation Not Supported ML Algorithm Library Not Supported Model Training Not Supported Neural Network Modeling Not Supported Self-Learning Not Supported Visualization Supported
Integrations Amazon SageMaker Debugger Not Supported AutoKeras Not Supported Comet Not Supported Comet LLM Not Supported Database Mart Not Supported Databricks Not Supported Gemma 3 Not Supported Gemma 4 Not Supported Google AI Edge Not Supported MLReef Not Supported PaliGemma 2 Not Supported Radicalbit Not Supported RunCode Not Supported Spell Not Supported StreamFlux Not Supported Unremot Not Supported Zepl Not Supported neptune.ai Not Supported Show More Integrations View All 1 Integration	Integrations Amazon SageMaker Debugger Supported AutoKeras Supported Comet Supported Comet LLM Supported Database Mart Supported Databricks Supported Gemma 3 Supported Gemma 4 Supported Google AI Edge Supported MLReef Supported PaliGemma 2 Supported Radicalbit Supported RunCode Supported Spell Supported StreamFlux Supported Unremot Supported Zepl Supported neptune.ai Supported Show More Integrations View All 51 Integrations
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