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Description

AWS Deep Learning AMIs (DLAMI) offer machine learning professionals and researchers a secure and curated collection of frameworks, tools, and dependencies to enhance deep learning capabilities in cloud environments. Designed for both Amazon Linux and Ubuntu, these Amazon Machine Images (AMIs) are pre-equipped with popular frameworks like TensorFlow, PyTorch, Apache MXNet, Chainer, Microsoft Cognitive Toolkit (CNTK), Gluon, Horovod, and Keras, enabling quick deployment and efficient operation of these tools at scale. By utilizing these resources, you can create sophisticated machine learning models for the development of autonomous vehicle (AV) technology, thoroughly validating your models with millions of virtual tests. The setup and configuration process for AWS instances is expedited, facilitating faster experimentation and assessment through access to the latest frameworks and libraries, including Hugging Face Transformers. Furthermore, the incorporation of advanced analytics, machine learning, and deep learning techniques allows for the discovery of trends and the generation of predictions from scattered and raw health data, ultimately leading to more informed decision-making. This comprehensive ecosystem not only fosters innovation but also enhances operational efficiency across various applications.

Description

Cloud images serve as operating system templates, with each instance initially being a perfect replica of the others. The unique attributes of each cloud instance are defined by user data, and cloud-init is the automated tool that applies this data to your instances. This includes various datasource and module references, along with numerous examples for easier implementation. Although cloud-init originated in Ubuntu, it has since been adapted for most major Linux distributions and FreeBSD. For providers of cloud images, cloud-init simplifies the variations among different cloud vendors automatically, ensuring that the official Ubuntu cloud images maintain consistency across all public and private cloud platforms. This uniformity allows users to deploy their applications without worrying about the underlying infrastructure differences.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
AWS Marketplace
AWS Neuron
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Google Cloud Platform
Joyent Triton
Microsoft Azure
MultiPass
Multipass
Oracle Cloud Infrastructure
PuppyGraph
Rackspace
VMware Cloud

Integrations

Amazon Web Services (AWS)
AWS Marketplace
AWS Neuron
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Google Cloud Platform
Joyent Triton
Microsoft Azure
MultiPass
Multipass
Oracle Cloud Infrastructure
PuppyGraph
Rackspace
VMware Cloud

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

Amazon

Founded

2006

Country

United States

Website

aws.amazon.com/machine-learning/amis/

Vendor Details

Company Name

cloud-init

Website

cloud-init.io

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Alternatives

AWS Neuron Reviews

AWS Neuron

Amazon Web Services

Alternatives

Multipass Reviews

Multipass

Canonical