Average Ratings 3 Ratings
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Description
The Microsoft Cognitive Toolkit (CNTK) is an open-source framework designed for high-performance distributed deep learning applications. It represents neural networks through a sequence of computational operations organized in a directed graph structure. Users can effortlessly implement and integrate various popular model architectures, including feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). CNTK employs stochastic gradient descent (SGD) along with error backpropagation learning, enabling automatic differentiation and parallel processing across multiple GPUs and servers. It can be utilized as a library within Python, C#, or C++ applications, or operated as an independent machine-learning tool utilizing its own model description language, BrainScript. Additionally, CNTK's model evaluation capabilities can be accessed from Java applications, broadening its usability. The toolkit is compatible with 64-bit Linux as well as 64-bit Windows operating systems. For installation, users have the option of downloading pre-compiled binary packages or building the toolkit from source code available on GitHub, which provides flexibility depending on user preferences and technical expertise. This versatility makes CNTK a powerful tool for developers looking to harness deep learning in their projects.
Description
Microsoft is actively advancing its R-related offerings, evident not only in the latest release of Machine Learning Server but also in the newest versions of Microsoft R Client and Microsoft R Open. Furthermore, R and Python integration is available within SQL Server Machine Learning Services for both Windows and Linux platforms, alongside R support in Azure SQL Database. The R components maintain backward compatibility, allowing users to execute existing R scripts on newer versions, as long as they do not rely on outdated packages or platforms that are no longer supported, or on known problems that necessitate workarounds or code modifications. Microsoft R Open serves as the enhanced version of R provided by Microsoft Corporation, with the most recent release, Microsoft R Open 4.0.2, built on the statistical language R-4.0.2, offering additional features for better performance, reproducibility, and platform compatibility. This version ensures compatibility with all packages, scripts, and applications built on R-4.0.2, making it a reliable choice for developers and data scientists alike. Overall, Microsoft's dedication to R fosters an environment of continuous improvement and support for its users.
API Access
Has API
API Access
Has API
Integrations
Microsoft Power Platform
AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure HDInsight
DataClarity Unlimited Analytics
Delinea Cloud Access Controller
Integrations
Microsoft Power Platform
AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure HDInsight
DataClarity Unlimited Analytics
Delinea Cloud Access Controller
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
Microsoft
Founded
1975
Country
United States
Website
docs.microsoft.com/en-us/cognitive-toolkit/
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
mran.microsoft.com/rro
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Product Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports