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Average Ratings 3 Ratings
Description
FASTBuild is an efficient, open-source build system compatible with Windows, Linux, and OS X. It offers robust capabilities for scalable compilation, caching, and network distribution. Whether utilized by major game studios or small indie developers, FASTBuild is actively employed in production environments to create software for a variety of platforms including PC, Mac, Linux, consoles, smartphones, and even retro systems. This powerful tool provides all necessary resources to enhance build speed, achieving improvements that can exceed 10 times compared to traditional build systems. Engineered with a focus on parallel compilation from the outset, FASTBuild's streamlined main build pipeline effectively allocates build tasks to worker threads, optimizing parallel processing. It circumvents the dependency issues often encountered with Visual Studio/MSBuild, ensuring a smoother build experience. Moreover, unlike Visual Studio, FASTBuild can meticulously control CPU core usage during builds, mitigating problems related to idle time and context switching, which ultimately leads to more efficient resource utilization. As a result, developers can expect quicker turnaround times and improved productivity throughout their build processes.
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
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Microsoft Dynamics 365 Finance
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Microsoft Power Platform
Integrations
AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform
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
FASTBuild
Website
www.fastbuild.org/docs/home.html
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
docs.microsoft.com/en-us/cognitive-toolkit/
Product Features
Build Automation
Automated Testing
Build Cache
Build Management Tools
Build Metrics
Change Only Compiling
Debugging Tools
Dependency Management
IDE Compatibility
Parallel Testing
Plugin Library
Source Code Management
Version Conflict Resolution
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization