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ease
features
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support

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Description

The Intel® Deep Learning SDK offers a comprehensive suite of tools designed for data scientists and software developers to create, train, and implement deep learning solutions effectively. This SDK includes both training and deployment tools that can function independently or in unison, providing a holistic approach to deep learning workflows. Users can seamlessly prepare their training data, design intricate models, and conduct training through automated experiments accompanied by sophisticated visualizations. Additionally, it streamlines the setup and operation of well-known deep learning frameworks that are tailored for Intel® hardware. The intuitive web user interface features a user-friendly wizard that assists in crafting deep learning models, complete with tooltips that guide users through every step of the process. Moreover, this SDK not only enhances productivity but also fosters innovation in the development of AI applications.

Description

Deep learning frameworks like TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have significantly enhanced the accessibility of deep learning by simplifying the design, training, and application of deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) offers a standardized method for deploying these deep-learning frameworks as a service on Kubernetes, ensuring smooth operation. The architecture of FfDL is built on microservices, which minimizes the interdependence between components, promotes simplicity, and maintains a stateless nature for each component. This design choice also helps to isolate failures, allowing for independent development, testing, deployment, scaling, and upgrading of each element. By harnessing the capabilities of Kubernetes, FfDL delivers a highly scalable, resilient, and fault-tolerant environment for deep learning tasks. Additionally, the platform incorporates a distribution and orchestration layer that enables efficient learning from large datasets across multiple compute nodes within a manageable timeframe. This comprehensive approach ensures that deep learning projects can be executed with both efficiency and reliability.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Caffe
Kubernetes
PyTorch
TensorFlow
Torch
ZETIC.ai

Integrations

Caffe
Kubernetes
PyTorch
TensorFlow
Torch
ZETIC.ai

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

Intel

Founded

1968

Country

United States

Website

software.intel.com/content/www/us/en/develop/articles/deep-learning-training-tool-release-notes.html

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/

Product Features

Deep Learning

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

Product Features

Deep Learning

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

Alternatives

Alternatives

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