Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.

Description

SHARK is a versatile and high-performance open-source library for machine learning, developed in C++. It encompasses a variety of techniques, including both linear and nonlinear optimization, kernel methods, neural networks, and more. This library serves as an essential resource for both practical applications and academic research endeavors. Built on top of Boost and CMake, SHARK is designed to be cross-platform, supporting operating systems such as Windows, Solaris, MacOS X, and Linux. It operates under the flexible GNU Lesser General Public License, allowing for broad usage and distribution. With a strong balance between flexibility, user-friendliness, and computational performance, SHARK includes a wide array of algorithms from diverse fields of machine learning and computational intelligence, facilitating easy integration and extension. Moreover, it boasts unique algorithms that, to the best of our knowledge, are not available in any other competing frameworks. This makes SHARK a particularly valuable tool for developers and researchers alike.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon EC2 UltraClusters
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Amazon SageMaker Studio Lab
Amazon SageMaker Unified Studio
Comet
Domino Enterprise MLOps Platform
EdgeCortix
Huawei Cloud ModelArts
IBM Distributed AI APIs
JFrog ML
Keepsake
NeevCloud
PaliGemma 2
PostgresML
Simplismart
SynapseAI
TensorWave
Unremot
io.net

Integrations

Amazon EC2 UltraClusters
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Amazon SageMaker Studio Lab
Amazon SageMaker Unified Studio
Comet
Domino Enterprise MLOps Platform
EdgeCortix
Huawei Cloud ModelArts
IBM Distributed AI APIs
JFrog ML
Keepsake
NeevCloud
PaliGemma 2
PostgresML
Simplismart
SynapseAI
TensorWave
Unremot
io.net

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

PyTorch

Founded

2016

Website

pytorch.org

Vendor Details

Company Name

SHARK

Founded

2018

Website

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

Product Features

Machine Learning

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

Product Features

Machine Learning

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

Alternatives

Core ML Reviews

Core ML

Apple

Alternatives

CloudShark Reviews

CloudShark

QA Cafe
DeepSpeed Reviews

DeepSpeed

Microsoft
Create ML Reviews

Create ML

Apple