MXNet

MXNet

The Apache Software Foundation
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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.

About

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.

Platforms Supported

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

Platforms Supported

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

Audience

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

Audience

Developers and researchers requiring an open-source deep learning framework for research prototyping and production

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

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 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

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

Keras
United States
keras.io

Company Information

The Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org

Alternatives

Alternatives

Caffe

Caffe

BAIR

Categories

Deep Learning Supported
Neural Network Supported

Categories

AI Development Supported
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 Supported
Cameralyze Supported
Flower Supported
Gradient Supported
Guild AI Supported
Horovod Supported
MLReef Supported
AWS Elastic Fabric Adapter (EFA) Not Supported
BentoML Supported
Databricks Supported
GPUEater Supported
LeaderGPU Not Supported
MLflow Supported
PaliGemma 2 Supported
Unremot Supported
Weights & Biases Supported
Zepl Supported
Zorro Supported
teX.ai Supported

Integrations

Amazon SageMaker Debugger Supported
Cameralyze Supported
Flower Supported
Gradient Supported
Guild AI Supported
Horovod Supported
MLReef Supported
AWS Elastic Fabric Adapter (EFA) Supported
BentoML Not Supported
Databricks Not Supported
GPUEater Not Supported
LeaderGPU Supported
MLflow Not Supported
PaliGemma 2 Not Supported
Unremot Not Supported
Weights & Biases Not Supported
Zepl Not Supported
Zorro Not Supported
teX.ai Not Supported
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