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What is TFLearn?

TFlearn is an intuitive and adaptable deep learning framework built on TensorFlow that aims to provide a more approachable API, thereby streamlining the experimentation process while maintaining complete compatibility with its foundational structure. Its design offers an easy-to-navigate high-level interface for crafting deep neural networks, supplemented with comprehensive tutorials and illustrative examples for user support. By enabling rapid prototyping with its modular architecture, TFlearn incorporates various built-in components such as neural network layers, regularizers, optimizers, and metrics. Users gain full visibility into TensorFlow, as all operations are tensor-centric and can function independently from TFLearn. The framework also includes powerful helper functions that aid in training any TensorFlow graph, allowing for the management of multiple inputs, outputs, and optimization methods. Additionally, the visually appealing graph visualization provides valuable insights into aspects like weights, gradients, and activations. The high-level API further accommodates a diverse array of modern deep learning architectures, including Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, and Generative networks, making it an invaluable resource for both researchers and developers. Furthermore, its extensive functionality fosters an environment conducive to innovation and experimentation in deep learning projects.

What is Blue Hexagon?

Our state-of-the-art real-time deep learning system is designed to achieve unmatched levels of detection speed, efficiency, and extensive coverage in the realm of cyber defense. We carefully train our neural networks utilizing a diverse spectrum of global threat intelligence sourced from various channels, including threat databases, the dark web, our own systems, and collaborative partnerships. Much like how layers in neural networks can identify images, our innovative neural network architecture adeptly identifies threats in both payloads and headers. Blue Hexagon Labs conducts thorough evaluations of our models' accuracy in the face of emerging threats in real-time, guaranteeing their reliability and precision. Our technology excels at detecting a wide array of cyber threats, encompassing file-based and fileless malware, exploits, command and control communications, and malicious domains across different operating systems such as Windows, Android, and Linux. Deep learning, a specialized field within machine learning, utilizes complex, multi-layered artificial neural networks to proficiently learn and represent data. As the cyber threat landscape continuously evolves, our platform is regularly updated to tackle new challenges and uphold its leading-edge capabilities. This ongoing commitment to innovation enables us to stay ahead of potential threats and safeguard digital environments effectively.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
GigaSECURE
Gigamon
Kubernetes
Microsoft Azure
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
GigaSECURE
Gigamon
Kubernetes
Microsoft Azure
TensorFlow

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

TFLearn

Company Website

tflearn.org

Company Facts

Organization Name

Blue Hexagon

Date Founded

2017

Company Location

United States

Company Website

bluehexagon.ai/products/

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

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