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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

Bayesforge™ is a specialized Linux machine image designed to assemble top-tier open source applications tailored for data scientists in need of sophisticated analytical tools, as well as for professionals in quantum computing and computational mathematics who wish to engage with key quantum computing frameworks. This image integrates well-known machine learning libraries like PyTorch and TensorFlow alongside open source tools from D-Wave, Rigetti, and platforms like IBM Quantum Experience and Google’s innovative quantum language Cirq, in addition to other leading quantum computing frameworks. For example, it features our quantum fog modeling framework and the versatile quantum compiler Qubiter, which supports cross-compilation across all significant architectures. Users can conveniently access all software through the Jupyter WebUI, which features a modular design that enables coding in Python, R, and Octave, enhancing flexibility in project development. Moreover, this comprehensive environment empowers researchers and developers to seamlessly blend classical and quantum computing techniques in their workflows.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace Yes 
AWS Neuron Yes 
Amazon EC2 G5 Instances Yes 
Amazon EC2 Inf1 Instances Yes 
Amazon EC2 P4 Instances Yes 
Amazon EC2 Trn1 Instances Yes 
Amazon EC2 Trn2 Instances Yes 
Amazon Web Services (AWS) Yes 
D-Wave No 
Google Cirq No 
IBM Quantum No 
Octave No 
PuppyGraph Yes 
PyTorch No 
Python No 
R No 
Rigetti Quantum Cloud Services (QCS) No 
TensorFlow No 

Integrations

AWS Marketplace Yes 
AWS Neuron No 
Amazon EC2 G5 Instances No 
Amazon EC2 Inf1 Instances No 
Amazon EC2 P4 Instances No 
Amazon EC2 Trn1 Instances No 
Amazon EC2 Trn2 Instances No 
Amazon Web Services (AWS) No 
D-Wave Yes 
Google Cirq Yes 
IBM Quantum Yes 
Octave Yes 
PuppyGraph No 
PyTorch Yes 
Python Yes 
R Yes 
Rigetti Quantum Cloud Services (QCS) Yes 
TensorFlow Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

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

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
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 No 
Live Training (Online) No 
In Person No 

Types of Training

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

Vendor Details

Company Name

Amazon

Founded

2006

Country

United States

Website

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

Vendor Details

Company Name

Quantum Programming Studio

Website

artiste-qb.net/bayesforge/

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

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