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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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.

Description

Steev serves as an AI training assistant designed to oversee your training operations, thus reducing the necessity for ongoing oversight while simultaneously boosting model efficacy. It conducts a thorough review and analysis of your code prior to the commencement of training, spotting potential mistakes, offering corrections, and proposing improved methods to enhance your workflow and results. Going further than simple observation, Steev takes initiative to modify training parameters and address issues before they become significant problems. It diligently monitors all crucial variables throughout the training process, providing immediate alerts when your input is required, which removes the need for frequent progress checks. With all essential features for more intelligent training integrated into Steev, it is fully prepared to use without any setup needed. You can explore Steev for free during its beta phase, allowing you to experience its capabilities without any commitment. This innovative tool is designed not only to optimize your training efficiency but also to empower you with insights that can lead to superior outcomes.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
LeaderGPU
MLReef
NVIDIA Triton Inference Server
Python

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
LeaderGPU
MLReef
NVIDIA Triton Inference Server
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

mxnet.apache.org

Vendor Details

Company Name

Steev

Country

United States

Website

www.steev.io

Product Features

Deep Learning

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

Product Features

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