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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

With Determined, you can engage in distributed training without needing to modify your model code, as it efficiently manages the provisioning of machines, networking, data loading, and fault tolerance. Our open-source deep learning platform significantly reduces training times to mere hours or minutes, eliminating the lengthy process of days or weeks. Gone are the days of tedious tasks like manual hyperparameter tuning, re-running failed jobs, and the constant concern over hardware resources. Our advanced distributed training solution not only surpasses industry benchmarks but also requires no adjustments to your existing code and seamlessly integrates with our cutting-edge training platform. Additionally, Determined features built-in experiment tracking and visualization that automatically logs metrics, making your machine learning projects reproducible and fostering greater collaboration within your team. This enables researchers to build upon each other's work and drive innovation in their respective fields, freeing them from the stress of managing errors and infrastructure. Ultimately, this streamlined approach empowers teams to focus on what they do best—creating and refining their models.

Description

A hybrid front-end efficiently switches between Gluon eager imperative mode and symbolic mode, offering both adaptability and speed. The framework supports scalable distributed training and enhances performance optimization for both research and real-world applications through its dual parameter server and Horovod integration. It features deep compatibility with Python and extends support to languages such as Scala, Julia, Clojure, Java, C++, R, and Perl. A rich ecosystem of tools and libraries bolsters MXNet, facilitating a variety of use-cases, including computer vision, natural language processing, time series analysis, and much more. Apache MXNet is currently in the incubation phase at The Apache Software Foundation (ASF), backed by the Apache Incubator. This incubation stage is mandatory for all newly accepted projects until they receive further evaluation to ensure that their infrastructure, communication practices, and decision-making processes align with those of other successful ASF initiatives. By engaging with the MXNet scientific community, individuals can actively contribute, gain knowledge, and find solutions to their inquiries. This collaborative environment fosters innovation and growth, making it an exciting time to be involved with MXNet.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS Elastic Fabric Adapter (EFA) No 
Amazon EC2 P4 Instances No 
Amazon Elastic Inference No 
Amazon S3 Yes 
Amazon SageMaker Yes 
Amazon SageMaker Debugger No 
Amazon SageMaker Model Building No 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Apache Spark Yes 
Flower No 
Google Cloud Platform Yes 
Gradient No 
Hadoop Yes 
LeaderGPU No 
MLflow Yes 
NVIDIA Triton Inference Server No 
Pachyderm Yes 
TensorFlow Yes 

Integrations

AWS Elastic Fabric Adapter (EFA) Yes 
Amazon EC2 P4 Instances Yes 
Amazon Elastic Inference Yes 
Amazon S3 No 
Amazon SageMaker No 
Amazon SageMaker Debugger Yes 
Amazon SageMaker Model Building Yes 
Amazon Web Services (AWS) No 
Apache Airflow No 
Apache Spark No 
Flower Yes 
Google Cloud Platform No 
Gradient Yes 
Hadoop No 
LeaderGPU Yes 
MLflow No 
NVIDIA Triton Inference Server Yes 
Pachyderm No 
TensorFlow No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Determined AI

Country

United States

Website

www.determined.ai/

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

mxnet.apache.org

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Alternatives

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