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Average Ratings 3 Ratings
Description
The Fink initiative aims to introduce the extensive realm of Unix open-source software to Darwin and Mac OS X environments. By modifying Unix applications to ensure they compile and operate seamlessly on Mac OS X—essentially "porting" them—we provide users with a unified distribution available for download. Utilizing Debian tools such as dpkg and apt-get, Fink offers robust binary package management capabilities. Users have the flexibility to either download precompiled binary packages or opt to build everything from source code. The project supplies both precompiled binary options and a fully automated system for building from source. While Mac OS X comes with merely a fundamental set of command-line tools, Fink enhances these tools and presents a variety of graphical applications designed for Linux and other Unix systems. With Fink, the compilation process becomes entirely automated, freeing users from the complexities of Makefiles and configure scripts, along with their various parameters. Additionally, the dependency management system ensures that all necessary libraries are automatically accounted for, streamlining the overall user experience. As a result, Fink significantly enriches the software ecosystem available to Mac OS X users.
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.
API Access
Has API
API Access
Has API
Integrations
Activeeon ProActive
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
DPKG
Debian
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Integrations
Activeeon ProActive
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
DPKG
Debian
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Pricing Details
Free
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
Fink
Website
www.finkproject.org
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
docs.microsoft.com/en-us/cognitive-toolkit/
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization