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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

TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 P5 Instances Yes 
Amazon Elastic Inference Yes 
Amazon SageMaker Studio Lab Yes 
Azure Marketplace Yes 
Bayesforge Yes 
Cameralyze Yes 
Comet Yes 
Fabric for Deep Learning (FfDL) Yes 
GPUEater Yes 
Groq Yes 
Label Studio Yes 
MLReef Yes 
NVIDIA Triton Inference Server Yes 
NeevCloud Yes 
Skyportal Yes 
io.net Yes 
spaCy Yes 

Integrations

Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 P5 Instances Yes 
Amazon Elastic Inference Yes 
Amazon SageMaker Studio Lab Yes 
Azure Marketplace Yes 
Bayesforge Yes 
Cameralyze Yes 
Comet Yes 
Fabric for Deep Learning (FfDL) Yes 
GPUEater Yes 
Groq Yes 
Label Studio Yes 
MLReef Yes 
NVIDIA Triton Inference Server Yes 
NeevCloud Yes 
Skyportal Yes 
io.net Yes 
spaCy Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

PyTorch

Founded

2016

Website

pytorch.org

Vendor Details

Company Name

TensorFlow

Founded

2015

Country

United States

Website

www.tensorflow.org

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization Yes 

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