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What is SHARK?

SHARK is a powerful and adaptable open-source library crafted in C++ for machine learning applications, featuring a comprehensive range of techniques such as linear and nonlinear optimization, kernel methods, and neural networks. This library is not only a significant asset for practical implementations but also for academic research projects. Built using Boost and CMake, SHARK is cross-platform and compatible with various operating systems, including Windows, Solaris, MacOS X, and Linux. It operates under the permissive GNU Lesser General Public License, ensuring widespread usage and distribution. SHARK strikes an impressive balance between flexibility, ease of use, and high computational efficiency, incorporating numerous algorithms from different domains of machine learning and computational intelligence, which simplifies integration and customization. Additionally, it offers distinctive algorithms that are, as far as we are aware, unmatched by other competing frameworks, enhancing its value as a resource for developers and researchers. As a result, SHARK stands out as an invaluable tool in the ever-evolving landscape of machine learning technologies.

What is Atinary SDLabs Platform?

Atinary's Self-Driving Labs (SDLabs) platform provides a no-code approach for artificial intelligence and machine learning, designed to revolutionize research and development workflows by enabling traditional laboratories to transition from manual experiments to fully autonomous experimentation. This innovative platform bolsters the design and improvement of experiments through a robust closed-loop system that integrates AI-generated hypotheses, predictions, and decision-making processes. Among its key functionalities are multi-objective optimization, effective database management, seamless workflow orchestration, and immediate data analysis. Users can define experimental parameters with specific limitations, allowing machine learning algorithms to guide the subsequent phases of the process, carry out experiments either manually or with robotic assistance, evaluate results, and refresh models with the most recent data, thereby accelerating the journey toward more efficient, cost-effective, and environmentally sustainable products. Furthermore, Atinary provides exclusive algorithms such as Emmental for addressing non-linear constrained optimization challenges, SeMOpt for facilitating transfer learning within Bayesian optimization, and Falcon, all of which significantly boost the platform's capabilities and performance. By utilizing these sophisticated tools, researchers are empowered to enhance their experimental workflows, fostering greater efficiency and driving innovation in their fields. Ultimately, the SDLabs platform represents a transformative shift in how laboratories approach experimentation, paving the way for groundbreaking discoveries.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

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

SHARK

Date Founded

2018

Company Website

image.diku.dk/shark/sphinx_pages/build/html/index.html

Company Facts

Organization Name

Atinary

Date Founded

2019

Company Location

Switzerland

Company Website

atinary.com/solutions/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

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