Average Ratings 0 Ratings
Average Ratings 3 Ratings
Description
Our real-time deep learning platform has been meticulously crafted to provide unparalleled speed in detection, effectiveness, and comprehensive coverage, establishing a groundbreaking benchmark for cyber defense. We harness global threat intelligence that we have meticulously gathered from various sources, including threat repositories, the dark web, our own deployments, and collaborations with partners, to train our neural networks. Similar to how layers of neural networks can recognize images in photographs, our unique neural network architecture is adept at pinpointing threats in both payloads and headers. Blue Hexagon Labs rigorously tests and confirms the precision of our models daily against emerging threats in the environment. Our advanced neural networks are capable of detecting a broad spectrum of threats, including both file and fileless malware, exploits, command and control communications, and malicious domains across multiple platforms such as Windows, Android, and Linux. Additionally, deep learning, a specialized area within machine learning, leverages complex, multi-layered artificial neural networks to comprehend and represent data effectively. This innovative approach enhances our ability to adapt to the ever-evolving landscape of cybersecurity challenges.
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
AI Skills Navigator
Alteryx
Amazon Web Services (AWS)
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
GigaSECURE
Gigamon
Kubernetes
Integrations
AI Skills Navigator
Alteryx
Amazon Web Services (AWS)
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
GigaSECURE
Gigamon
Kubernetes
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
Blue Hexagon
Founded
2017
Country
United States
Website
bluehexagon.ai/products/
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