ConvNetJS vs. Ray Comparison


ConvNetJS	Ray Anyscale	+	+
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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 Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
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 Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Developers, professionals and researchers seeking a solution for training deep learning models	Audience ML and AI Engineers, Software Developers
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 Free Open source. Consumption-based. Free Version Supported Free Trial 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 Supported In Person Supported
Company Information ConvNetJS cs.stanford.edu/people/karpathy/convnetjs/	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives Microsoft Cognitive Toolkit Microsoft	Alternatives Anyscale
Neuralhub	Horovod
TFLearn	Determined AI
Zebra by Mipsology Mipsology	Neuralhub
Deci Deci AI View All	Automaton AI View All
Categories Deep Learning Supported Neural Network Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Amazon EC2 Trn2 Instances Not Supported Amazon EKS Not Supported Amazon SageMaker Not Supported Amazon Web Services (AWS) Not Supported Anyscale Not Supported Apache Airflow Not Supported Azure Kubernetes Service (AKS) Not Supported Dask Not Supported Feast Not Supported Flyte Not Supported Google Kubernetes Engine (GKE) Not Supported Kubernetes Not Supported LanceDB Not Supported MLflow Not Supported PyTorch Not Supported Python Not Supported Snowflake Not Supported TensorFlow Not Supported Union Cloud Not Supported io.net Not Supported Show More Integrations View All 1 Integration	Integrations Amazon EC2 Trn2 Instances Supported Amazon EKS Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Anyscale Supported Apache Airflow Supported Azure Kubernetes Service (AKS) Supported Dask Supported Feast Supported Flyte Supported Google Kubernetes Engine (GKE) Supported Kubernetes Supported LanceDB Supported MLflow Supported PyTorch Supported Python Supported Snowflake Supported TensorFlow Supported Union Cloud Supported io.net Supported Show More Integrations View All 22 Integrations
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