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What is Google Cloud Deep Learning VM Image?

Rapidly establish a virtual machine on Google Cloud for your deep learning initiatives by utilizing the Deep Learning VM Image, which streamlines the deployment of a VM pre-loaded with crucial AI frameworks on Google Compute Engine. This option enables you to create Compute Engine instances that include widely-used libraries like TensorFlow, PyTorch, and scikit-learn, so you don't have to worry about software compatibility issues. Moreover, it allows you to easily add Cloud GPU and Cloud TPU capabilities to your setup. The Deep Learning VM Image is tailored to accommodate both state-of-the-art and popular machine learning frameworks, granting you access to the latest tools. To boost the efficiency of model training and deployment, these images come optimized with the most recent NVIDIA® CUDA-X AI libraries and drivers, along with the Intel® Math Kernel Library. By leveraging this service, you can quickly get started with all the necessary frameworks, libraries, and drivers already installed and verified for compatibility. Additionally, the Deep Learning VM Image enhances your experience with integrated support for JupyterLab, promoting a streamlined workflow for data science activities. With these advantageous features, it stands out as an excellent option for novices and seasoned experts alike in the realm of machine learning, ensuring that everyone can make the most of their projects. Furthermore, the ease of use and extensive support make it a go-to solution for anyone looking to dive into AI development.

What is Datatron?

Datatron offers a suite of tools and features designed from the ground up to facilitate the practical implementation of machine learning in production environments. Many teams discover that deploying models involves more complexity than simply executing manual tasks. With Datatron, you gain access to a unified platform that oversees all your machine learning, artificial intelligence, and data science models in a production setting. Our solution allows you to automate, optimize, and expedite the production of your machine learning models, ensuring they operate seamlessly and effectively. Data scientists can leverage various frameworks to develop optimal models, as we support any framework you choose to utilize, including TensorFlow, H2O, Scikit-Learn, and SAS. You can easily browse through models uploaded by your data scientists, all accessible from a centralized repository. Within just a few clicks, you can establish scalable model deployments, and you have the flexibility to deploy models using any programming language or framework of your choice. This capability enhances your model performance, leading to more informed and strategic decision-making. By streamlining the process of model deployment, Datatron empowers teams to focus on innovation and results.

Media

Media

Integrations Supported

Google Cloud Platform
TensorFlow
Chainer
Google Cloud TPU
Google Compute Engine
JupyterLab
MXNet
NVIDIA DRIVE
PyTorch

Integrations Supported

Google Cloud Platform
TensorFlow
Amazon Web Services (AWS)
H2O.ai
Hadoop
Microsoft Azure
MySQL
PostgreSQL
SAS Asset Performance Analytics
Salesforce
Teradata VantageCloud
Wipro Promax

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/deep-learning-vm

Company Facts

Organization Name

Datatron

Date Founded

2016

Company Location

United States

Company Website

www.datatron.com/platform/

Categories and Features

AI Infrastructure

Not specified

Deep Learning

Not specified

Categories and Features

AI Governance

Not specified

Machine Learning

Not specified

Model Risk Management

Not specified

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