Ratings and Reviews 3 Ratings

Total
ease
features
design
support

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Gemini Enterprise Agent Platform Reviews & Ratings
    961 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    355 Ratings
    Company Website
  • ActCAD Software Reviews & Ratings
    401 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Resco Mobile App Development Toolkit Reviews & Ratings
    2 Ratings
    Company Website
  • JetBrains Junie Reviews & Ratings
    12 Ratings
    Company Website
  • Teradata VantageCloud Reviews & Ratings
    1,105 Ratings
    Company Website
  • Windsurf Editor Reviews & Ratings
    168 Ratings
    Company Website
  • NetBrain Reviews & Ratings
    247 Ratings
    Company Website

What is Microsoft Cognitive Toolkit?

The Microsoft Cognitive Toolkit (CNTK) is an open-source framework that facilitates high-performance distributed deep learning applications. It models neural networks using a series of computational operations structured in a directed graph format. Developers can easily implement and combine numerous well-known model architectures such as feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). By employing stochastic gradient descent (SGD) and error backpropagation learning, CNTK supports automatic differentiation and allows for parallel processing across multiple GPUs and server environments. The toolkit can function as a library within Python, C#, or C++ applications, or it can be used as a standalone machine-learning tool that utilizes its own model description language, BrainScript. Furthermore, CNTK's model evaluation features can be accessed from Java applications, enhancing its versatility. It is compatible with 64-bit Linux and 64-bit Windows operating systems. Users have the flexibility to either download pre-compiled binary packages or build the toolkit from the source code available on GitHub, depending on their preferences and technical expertise. This broad compatibility and adaptability make CNTK an invaluable resource for developers aiming to implement deep learning in their projects, ensuring that they can tailor their tools to meet specific needs effectively.

What is Fabric for Deep Learning (FfDL)?

Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have greatly improved the ease with which deep learning models can be designed, trained, and utilized. Fabric for Deep Learning (FfDL, pronounced "fiddle") provides a unified approach for deploying these deep-learning frameworks as a service on Kubernetes, facilitating seamless functionality. The FfDL architecture is constructed using microservices, which reduces the reliance between components, enhances simplicity, and ensures that each component operates in a stateless manner. This architectural choice is advantageous as it allows failures to be contained and promotes independent development, testing, deployment, scaling, and updating of each service. By leveraging Kubernetes' capabilities, FfDL creates an environment that is highly scalable, resilient, and capable of withstanding faults during deep learning operations. Furthermore, the platform includes a robust distribution and orchestration layer that enables efficient processing of extensive datasets across several compute nodes within a reasonable time frame. Consequently, this thorough strategy guarantees that deep learning initiatives can be carried out with both effectiveness and dependability, paving the way for innovative advancements in the field.

Media

Media

Integrations Supported

AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Caffe
Kubernetes
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform
PyTorch
TensorFlow
Torch

Integrations Supported

AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Caffe
Kubernetes
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform
PyTorch
TensorFlow
Torch

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

docs.microsoft.com/en-us/cognitive-toolkit/

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

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

Categories and Features

Deep Learning

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

Categories and Features

Deep Learning

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

Popular Alternatives

Popular Alternatives

Neural Designer Reviews & Ratings

Neural Designer

Artelnics